In this talk we discuss the role of coordination models and technologies in the engineering of complex computational systems.
Complex Systems Physics Meeting IMT-UNIBO
Dipartimento di Fisica e Astronomia, Università di Bologna
Bologna, Italy, 15/02/2018
Complexity & Interaction: Blurring Borders between Physical, Computational, a...Andrea Omicini
Complex systems of any sorts are characterised by autonomous components interacting with each other in a non-trivial way. In this paper we discuss how the views on complexity are evolving in fields like physics, social sciences, and computer science, and – most significantly – how they are converging. In particular, we focus on the role of interaction as the most important dimension for modelling complexity, and discuss first how coordination via mediated interaction could determine the general dynamics of complex software system, then how this applies to complex socio-technical systems like social networks.
Complexity & Interaction: Blurring Borders between Physical, Computational, a...Andrea Omicini
Complex systems of any kind are characterised by autonomous components interacting with each other in a non-trivial way. In this short talk, we discuss how the views on complexity are evolving in fields like physics, social sciences, and computer science, and – most significantly – how they are converging. In particular, we focus on the role of interaction as the foremost dimension for modelling complexity, and discuss first how coordination via mediated interaction could determine the general dynamics of complex software system, then how this applies to complex socio-technical systems like social networks.
Coordination for Situated MAS: Towards an Event-driven ArchitectureAndrea Omicini
Complex software systems modelled as multi-agent systems (MAS) are characterised by activities that are generated either by agents, or by the environment in its most general acceptation — that is, environmental resources and the spatio-temporal fabric. Modelling and engineering complex MAS – such as pervasive, adaptive, and situated MAS – requires then to properly handle diverse classes of events: agent operations, resource events, spatio-temporal situation. In this talk we first devise out the requirements and sketch a software architecture for an agent middleware based on boundary artefacts such as agent coordination contexts, resource transducers, and space-time transducers. Then we discuss its system architecture exploiting agent, environment & space-time managers, and show some examples of a concrete architecture based on the TuCSoN middleware for MAS coordination.
From Coordination to Semantic Self-Organisation: A Perspective on the Enginee...Andrea Omicini
After briefly recapitulating the classical lines of the literature on coordination models, we discuss the new lines of research that aim at addressing the coordination of complex systems, then focus on mechanisms and patterns of coordination for self-organising systems. The notions of semantic coordination and self-organising coordination are defined and shortly discussed, then a vision of SOSC (self-organising semantic coordination) is presented, along with some insights over available technologies and possible scenarios for SOSC.
[Lecture at the PhD Mini-school, 11th National Workshop "From Objects to Agents" (WOA 2010) — 05/09/2010, Bologna, Italy.
Autonomy, Interaction & Complexity in Computational Systems. Preliminary NotesAndrea Omicini
The issues of autonomy do not end with autonomous components. Autonomous systems are complex self-organising systems where interaction plays an essential role. Here we discuss some early thoughts on autonomy, interaction, and complexity in artificial systems, and suggest that nature-inspired coordination models should work as the main sources of technologies.
Nature-inspired Coordination: Current Status and Research TrendsAndrea Omicini
Tutorial @WI 2017, Leipzig, 23 August 2017
Andrea Omicini & Stefano Mariani, Lecturers
Originating from closed parallel systems, coordination models and technologies gained in expressive power so as to deal with complex distributed systems. In particular, nature-inspired models of coordination emerged in the last decade as the most effective approaches to tackle the complexity of pervasive, intelligent, and self-* systems.
In the first part of the tutorial we introduce the basic notions of coordination and coordination model, and relate them to the notions of interaction and complexity. Then, the most relevant nature-inspired coordination (NIC) models are discussed, along with their relationship with the many facets of tuple-based models. In the third part we discuss the main open issues and explore the trends for future development of NIC. Finally, as a case study, we focus on MoK (Molecules of Knowledge), a NIC model for knowledge self-organisation, where data and information autonomously aggregate and spread toward knowledge prosumers.
Complexity & Interaction: Blurring Borders between Physical, Computational, a...Andrea Omicini
Complex systems of any sorts are characterised by autonomous components interacting with each other in a non-trivial way. In this paper we discuss how the views on complexity are evolving in fields like physics, social sciences, and computer science, and – most significantly – how they are converging. In particular, we focus on the role of interaction as the most important dimension for modelling complexity, and discuss first how coordination via mediated interaction could determine the general dynamics of complex software system, then how this applies to complex socio-technical systems like social networks.
Complexity & Interaction: Blurring Borders between Physical, Computational, a...Andrea Omicini
Complex systems of any kind are characterised by autonomous components interacting with each other in a non-trivial way. In this short talk, we discuss how the views on complexity are evolving in fields like physics, social sciences, and computer science, and – most significantly – how they are converging. In particular, we focus on the role of interaction as the foremost dimension for modelling complexity, and discuss first how coordination via mediated interaction could determine the general dynamics of complex software system, then how this applies to complex socio-technical systems like social networks.
Coordination for Situated MAS: Towards an Event-driven ArchitectureAndrea Omicini
Complex software systems modelled as multi-agent systems (MAS) are characterised by activities that are generated either by agents, or by the environment in its most general acceptation — that is, environmental resources and the spatio-temporal fabric. Modelling and engineering complex MAS – such as pervasive, adaptive, and situated MAS – requires then to properly handle diverse classes of events: agent operations, resource events, spatio-temporal situation. In this talk we first devise out the requirements and sketch a software architecture for an agent middleware based on boundary artefacts such as agent coordination contexts, resource transducers, and space-time transducers. Then we discuss its system architecture exploiting agent, environment & space-time managers, and show some examples of a concrete architecture based on the TuCSoN middleware for MAS coordination.
From Coordination to Semantic Self-Organisation: A Perspective on the Enginee...Andrea Omicini
After briefly recapitulating the classical lines of the literature on coordination models, we discuss the new lines of research that aim at addressing the coordination of complex systems, then focus on mechanisms and patterns of coordination for self-organising systems. The notions of semantic coordination and self-organising coordination are defined and shortly discussed, then a vision of SOSC (self-organising semantic coordination) is presented, along with some insights over available technologies and possible scenarios for SOSC.
[Lecture at the PhD Mini-school, 11th National Workshop "From Objects to Agents" (WOA 2010) — 05/09/2010, Bologna, Italy.
Autonomy, Interaction & Complexity in Computational Systems. Preliminary NotesAndrea Omicini
The issues of autonomy do not end with autonomous components. Autonomous systems are complex self-organising systems where interaction plays an essential role. Here we discuss some early thoughts on autonomy, interaction, and complexity in artificial systems, and suggest that nature-inspired coordination models should work as the main sources of technologies.
Nature-inspired Coordination: Current Status and Research TrendsAndrea Omicini
Tutorial @WI 2017, Leipzig, 23 August 2017
Andrea Omicini & Stefano Mariani, Lecturers
Originating from closed parallel systems, coordination models and technologies gained in expressive power so as to deal with complex distributed systems. In particular, nature-inspired models of coordination emerged in the last decade as the most effective approaches to tackle the complexity of pervasive, intelligent, and self-* systems.
In the first part of the tutorial we introduce the basic notions of coordination and coordination model, and relate them to the notions of interaction and complexity. Then, the most relevant nature-inspired coordination (NIC) models are discussed, along with their relationship with the many facets of tuple-based models. In the third part we discuss the main open issues and explore the trends for future development of NIC. Finally, as a case study, we focus on MoK (Molecules of Knowledge), a NIC model for knowledge self-organisation, where data and information autonomously aggregate and spread toward knowledge prosumers.
Course on "Nature-inspired Coordination Models for Complex Distributed Systems", Part I.
CUSO Seminar on Coordination Models, 20 - 21 November 2014, Fribourg, CH
Introductory tutorial on the foundations of agents and multi-agent systems at the 18th European Agent Systems Summer School (EASSS 2016) – 25 July 2016, Catania, Italy
Course on "Nature-inspired Coordination Models for Complex Distributed Systems", Part II.
CUSO Seminar on Coordination Models, 20 - 21 November 2014, Fribourg, CH
The Distributed Autonomy. Software Abstractions and Technologies for Autonomo...Andrea Omicini
In this short talk, we elaborate on the software issues of autonomous systems, by focussing on their interpretation as multi-agent systems. We suggest that a notion of distributed autonomy needs to be investigated – in particular in the area of (L)AWS – for its potential implications in terms of uncertainty of responsibility and liability.
On the Integration of Symbolic and Sub-symbolic – Explaining by DesignAndrea Omicini
The more intelligent systems based on sub-symbolic techniques pervade our everyday lives, the less human can understand them. This is why symbolic approaches are getting more and more attention in the general effort to make AI interpretable, explainable, and trustable. Understanding the current state of the art of AI techniques integrating symbolic and sub-symbolic approaches is then of paramount importance, nowadays—in particular in the XAI perspective. In this talk we first provides an overview of the main symbolic/sub-symbolic integration techniques, focussing in particular on those targeting explainable AI systems. Then we expand the notion of “explainability by design” to the realm of multi-agent systems, where XAI techniques can play a key role in the engineering of intelligent systems.
Not just for humans: Explanation for agent-to-agent communicationAndrea Omicini
Once precisely defined so as to include just the explanation’s act, the notion of explanation should be regarded as a central notion in the engineering of intelligent system—not just as an add-on to make them understandable to humans. Based on symbolic AI techniques to match intuitive and rational cognition, explanation should be exploited as a fundamental tool for inter-agent communication among heterogeneous agents in open multi-agent systems. More generally, explanation-ready agents should work as the basic components in the engineering of intelligent systems integrating both symbolic and sub-/non-symbolic AI techniques.
Presented by Andrea Omicini @ AIxIA 2020 Discussion Paper Workshop
Nature-inspired Coordination for Complex Distributed SystemsAndrea Omicini
Originating from closed parallel systems, coordination models and technologies gained in expressive power so to deal with open distributed systems. In particular, nature-inspired models of coordination emerged in the last decade as the most effective approaches to tackle the complexity of pervasive, intelligent, and self-* systems. In this talk we survey the most relevant nature-inspired coordination models, discuss the main open issues, and explore the potential for their future development.
[Invited Talk @ IDC 2012, Calabria, Italy, 26/9/2012]
Advanced Coordination Techniques: Experiments with TuCSoN and ReSpecTStefano Mariani
Distributed systems are more about interaction than computation: thus, they need coordination abstractions and techniques for managing the associated space of interaction.
Inspired to the archetypal Linda model, TuCSoN is a coordination model and technology providing tuple-based coordination services to (mobile) software agents through the notion of tuple centre—that is, a programmable tuple space. ReSpecT is a coordination language enabling run-time programmability of TuCSoN tuple centres—that is, of the coordination primitives and laws enabling and constraining interaction.
In this seminar TuCSoN and ReSpecT are used as the reference models and technologies for experimenting advanced coordination techniques for distributed and mobile programming of intelligent and pervasive multi-agent systems.
The conventional use of technology at an administrative level constitutes much more than its usage as
an engineered object. Factual evidence of this was established through a study conducted at LSE, to
analyze how the ultimate outcome of technology in practice is largely determined by the interactions
that technology has with its users coming from different institutionalized environments. To do so, the
popular technical deterministic approach is extended, by adopting a socio-political lens aimed at
understanding “technology in practice”. The social constructivist and the structurational stance, put
together, highlight the delicate intricacies that take place during the recursive interaction between the
user and technology, which shapes technology into a socially politicized object.
Micro-intelligence for the IoT: Teaching the Old Logic Dog New Programming Tr...Andrea Omicini
New application scenarios for pervasive intelligent systems open novel perspectives for logic-based approaches, in particular when coupled with agent-based technologies and methods. In this explorative talk we provide some examples of how logic programming and its extensions can work as sources of micro-intelligence for the IoT, at both the individual and the collective level, along with an overall architectural view of IoT systems exploiting logic-based technologies.
The Autonomy of Automated Systems: Social Systems and the Multi-level AutonomyAndrea Omicini
In this part of the presentation, we extend our discussion of the notion of autonomy to include multi-agent, coordinated, and self-organising systems, by introducing the notion of multi-level autonomy.
Models and Concepts for Socio-technical Complex Systems: Towards Fractal Soci...Vincenzo De Florio
We introduce fractal social organizations—a novel class of socio-technical complex systems characterized
by a distributed, bio-inspired, hierarchical architecture. Based on a same building block that is recursively
applied at different layers, said systems provide a homogeneous way to model collective behaviors of
different complexity and scale. Key concepts and principles are enunciated by means of a case study and a
simple formalism. As preliminary evidence of the adequacy of the assumptions underlying our systems here
we define and study an algebraic model for a simple class of social organizations. We show how despite its
generic formulation, geometric representations of said model exhibit the spontaneous emergence of complex
hierarchical and modular patterns characterized by structured addition of complexity and fractal nature—
which closely correspond to the distinctive architectural traits of our fractal social organizations. Some
reflections on the significance of these results and a view to the next steps of our research conclude this
contribution.
Coordination Models and Technologies toward Self-Organising SystemsAndrea Omicini
Starting from the pioneering work on Linda and Gamma, coordination models and languages have gone through an amazing evolution process over the years. From closed to open systems, from parallel computing to multi-agent systems and from database integration to knowledge-intensive environments, coordination abstractions and technologies have gained in relevance and power in those scenarios where complexity has become a key factor. In this lecture, we outline and motivate 25 years of evolution of coordination models and discuss their potential perspectives in the future of artificial systems.
[Lecture at the AWARENESS Virtual Lecture Series]
Feedback thought at the intersection of systems and design scienceDaniel Guzzo
Paper title: Feedback thought at the intersection of systems and design science
Authors: Igor Czermainski de Oliveira, Daniel Guzzo and Daniela C. A. Pigosso
Abstract:
This paper explores the interplay of feedback principles in design and systems science. From their roots in engineering, biology, and economics, it investigates intersections between design, cybernetics and servomechanisms. The synthesis emphasizes the need for considering feedback in anticipating unintended consequences and proposes an integrative view reconciling fundamental assumptions from the different fields through simulation. This holistic approach underscores the pivotal role of feedback in understanding and addressing complex phenomena, such as rebound effects, in design science.
DESIGN 2024 Conference presentation
Explainable Pervasive Intelligence with Self-explaining AgentsAndrea Omicini
Pervasiveness of ICT resources along with the promise of ubiquitous intelligence is pushing hard both our demand and our fears of AI: demand mandates for the ability to inject intelligence ubiquitously; fears compel the behaviour of intelligent systems to be observable, explainable, and accountable. Whereas the first wave of the new "AI Era" was mostly heralded by sub-symbolic approaches, features like explainability are better provided by symbolic techniques. In particular, the notion of explanation should be regarded as a core notion for intelligent systems, rather than just an add-on to make them understandable to humans. Based on symbolic AI techniques to match intuitive and rational cognition, explanation should then be regarded as a fundamental tool for inter-agent communication among heterogeneous intelligent agents in open multi-agent systems. More generally, self-explaining agents should work as the basic components in the engineering of intelligent systems integrating both symbolic and sub-/non-symbolic AI techniques.
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Course on "Nature-inspired Coordination Models for Complex Distributed Systems", Part I.
CUSO Seminar on Coordination Models, 20 - 21 November 2014, Fribourg, CH
Introductory tutorial on the foundations of agents and multi-agent systems at the 18th European Agent Systems Summer School (EASSS 2016) – 25 July 2016, Catania, Italy
Course on "Nature-inspired Coordination Models for Complex Distributed Systems", Part II.
CUSO Seminar on Coordination Models, 20 - 21 November 2014, Fribourg, CH
The Distributed Autonomy. Software Abstractions and Technologies for Autonomo...Andrea Omicini
In this short talk, we elaborate on the software issues of autonomous systems, by focussing on their interpretation as multi-agent systems. We suggest that a notion of distributed autonomy needs to be investigated – in particular in the area of (L)AWS – for its potential implications in terms of uncertainty of responsibility and liability.
On the Integration of Symbolic and Sub-symbolic – Explaining by DesignAndrea Omicini
The more intelligent systems based on sub-symbolic techniques pervade our everyday lives, the less human can understand them. This is why symbolic approaches are getting more and more attention in the general effort to make AI interpretable, explainable, and trustable. Understanding the current state of the art of AI techniques integrating symbolic and sub-symbolic approaches is then of paramount importance, nowadays—in particular in the XAI perspective. In this talk we first provides an overview of the main symbolic/sub-symbolic integration techniques, focussing in particular on those targeting explainable AI systems. Then we expand the notion of “explainability by design” to the realm of multi-agent systems, where XAI techniques can play a key role in the engineering of intelligent systems.
Not just for humans: Explanation for agent-to-agent communicationAndrea Omicini
Once precisely defined so as to include just the explanation’s act, the notion of explanation should be regarded as a central notion in the engineering of intelligent system—not just as an add-on to make them understandable to humans. Based on symbolic AI techniques to match intuitive and rational cognition, explanation should be exploited as a fundamental tool for inter-agent communication among heterogeneous agents in open multi-agent systems. More generally, explanation-ready agents should work as the basic components in the engineering of intelligent systems integrating both symbolic and sub-/non-symbolic AI techniques.
Presented by Andrea Omicini @ AIxIA 2020 Discussion Paper Workshop
Nature-inspired Coordination for Complex Distributed SystemsAndrea Omicini
Originating from closed parallel systems, coordination models and technologies gained in expressive power so to deal with open distributed systems. In particular, nature-inspired models of coordination emerged in the last decade as the most effective approaches to tackle the complexity of pervasive, intelligent, and self-* systems. In this talk we survey the most relevant nature-inspired coordination models, discuss the main open issues, and explore the potential for their future development.
[Invited Talk @ IDC 2012, Calabria, Italy, 26/9/2012]
Advanced Coordination Techniques: Experiments with TuCSoN and ReSpecTStefano Mariani
Distributed systems are more about interaction than computation: thus, they need coordination abstractions and techniques for managing the associated space of interaction.
Inspired to the archetypal Linda model, TuCSoN is a coordination model and technology providing tuple-based coordination services to (mobile) software agents through the notion of tuple centre—that is, a programmable tuple space. ReSpecT is a coordination language enabling run-time programmability of TuCSoN tuple centres—that is, of the coordination primitives and laws enabling and constraining interaction.
In this seminar TuCSoN and ReSpecT are used as the reference models and technologies for experimenting advanced coordination techniques for distributed and mobile programming of intelligent and pervasive multi-agent systems.
The conventional use of technology at an administrative level constitutes much more than its usage as
an engineered object. Factual evidence of this was established through a study conducted at LSE, to
analyze how the ultimate outcome of technology in practice is largely determined by the interactions
that technology has with its users coming from different institutionalized environments. To do so, the
popular technical deterministic approach is extended, by adopting a socio-political lens aimed at
understanding “technology in practice”. The social constructivist and the structurational stance, put
together, highlight the delicate intricacies that take place during the recursive interaction between the
user and technology, which shapes technology into a socially politicized object.
Micro-intelligence for the IoT: Teaching the Old Logic Dog New Programming Tr...Andrea Omicini
New application scenarios for pervasive intelligent systems open novel perspectives for logic-based approaches, in particular when coupled with agent-based technologies and methods. In this explorative talk we provide some examples of how logic programming and its extensions can work as sources of micro-intelligence for the IoT, at both the individual and the collective level, along with an overall architectural view of IoT systems exploiting logic-based technologies.
The Autonomy of Automated Systems: Social Systems and the Multi-level AutonomyAndrea Omicini
In this part of the presentation, we extend our discussion of the notion of autonomy to include multi-agent, coordinated, and self-organising systems, by introducing the notion of multi-level autonomy.
Models and Concepts for Socio-technical Complex Systems: Towards Fractal Soci...Vincenzo De Florio
We introduce fractal social organizations—a novel class of socio-technical complex systems characterized
by a distributed, bio-inspired, hierarchical architecture. Based on a same building block that is recursively
applied at different layers, said systems provide a homogeneous way to model collective behaviors of
different complexity and scale. Key concepts and principles are enunciated by means of a case study and a
simple formalism. As preliminary evidence of the adequacy of the assumptions underlying our systems here
we define and study an algebraic model for a simple class of social organizations. We show how despite its
generic formulation, geometric representations of said model exhibit the spontaneous emergence of complex
hierarchical and modular patterns characterized by structured addition of complexity and fractal nature—
which closely correspond to the distinctive architectural traits of our fractal social organizations. Some
reflections on the significance of these results and a view to the next steps of our research conclude this
contribution.
Coordination Models and Technologies toward Self-Organising SystemsAndrea Omicini
Starting from the pioneering work on Linda and Gamma, coordination models and languages have gone through an amazing evolution process over the years. From closed to open systems, from parallel computing to multi-agent systems and from database integration to knowledge-intensive environments, coordination abstractions and technologies have gained in relevance and power in those scenarios where complexity has become a key factor. In this lecture, we outline and motivate 25 years of evolution of coordination models and discuss their potential perspectives in the future of artificial systems.
[Lecture at the AWARENESS Virtual Lecture Series]
Feedback thought at the intersection of systems and design scienceDaniel Guzzo
Paper title: Feedback thought at the intersection of systems and design science
Authors: Igor Czermainski de Oliveira, Daniel Guzzo and Daniela C. A. Pigosso
Abstract:
This paper explores the interplay of feedback principles in design and systems science. From their roots in engineering, biology, and economics, it investigates intersections between design, cybernetics and servomechanisms. The synthesis emphasizes the need for considering feedback in anticipating unintended consequences and proposes an integrative view reconciling fundamental assumptions from the different fields through simulation. This holistic approach underscores the pivotal role of feedback in understanding and addressing complex phenomena, such as rebound effects, in design science.
DESIGN 2024 Conference presentation
Explainable Pervasive Intelligence with Self-explaining AgentsAndrea Omicini
Pervasiveness of ICT resources along with the promise of ubiquitous intelligence is pushing hard both our demand and our fears of AI: demand mandates for the ability to inject intelligence ubiquitously; fears compel the behaviour of intelligent systems to be observable, explainable, and accountable. Whereas the first wave of the new "AI Era" was mostly heralded by sub-symbolic approaches, features like explainability are better provided by symbolic techniques. In particular, the notion of explanation should be regarded as a core notion for intelligent systems, rather than just an add-on to make them understandable to humans. Based on symbolic AI techniques to match intuitive and rational cognition, explanation should then be regarded as a fundamental tool for inter-agent communication among heterogeneous intelligent agents in open multi-agent systems. More generally, self-explaining agents should work as the basic components in the engineering of intelligent systems integrating both symbolic and sub-/non-symbolic AI techniques.
Blockchain for Intelligent Systems: Research PerspectivesAndrea Omicini
We summarise and compare features of MAS and BCT, and discuss how they could be fruitfully integrated in the engineering of intelligent systems by adopting a long-term research perspective.
Injecting (Micro)Intelligence in the IoT: Logic-based Approaches for (M)MASAndrea Omicini
Pervasiveness of ICT resources along with the promise of ubiquitous intelligence is pushing hard both our demand and our fears of AI: demand mandates for the ability to inject (micro) intelligence ubiquitously, fears compel the behaviour of intelligent systems to be observable, explainable, and accountable.
Whereas the first wave of the new "AI Era" was mostly heralded by non-symbolic approaches, features like explainability are better provided by symbolic techniques.
In this talk we focus on logic-based approaches, and discuss their potential in pervasive scenarios like the IoT and open (M)MAS along with our latest results in the field.
Andrea Omicini, Roberta Calegari
Invited Talk
MMAS 2018, Stockholm, Sweden, 14 July 2018
Novel Opportunities for Tuple-based Coordination: XPath, the Blockchain, and ...Andrea Omicini
The increasing maturity of some well-established technologies – such as XPath – along with the sharp rise of brand-new ones – i.e. the blockchain – presents new opportunities to researchers in the field of multi-agent coordination. In this talk we briefly discuss a few technologies which, once suitably interpreted and integrated, have the potential to impact the very roots of tuple-based coordination as it stems from the archetypal LINDA model.
Logic Programming as a Service (LPaaS): Intelligence for the IoTAndrea Omicini
Talk @ ICNSC 2017, Calabria, Italy, 16 May 2017
Abstract: The widespread diffusion of low-cost computing devices, such as Arduino boards and Raspberry Pi, along with improvements of Cloud computing platforms, are paving the way towards a whole new set of opportunities for Internet of Things (IoT) applications and services. Varying degrees of intelligence are often required for supporting adaptation and self-management—yet, they should be provided in a light-weight, easy to use and customise, highly-interoperable way. Accordingly, in this paper we explore the idea of Logic Programming as a Service (LPaaS) as a novel and promising re-interpretation of distributed logic programming in the IoT era. After introducing the reference context and motivating scenarios of LPaaS as a key enabling technology for intelligent IoT, we define the LPaaS general system architecture. Then, we present a prototype implementation built on top of the tuProlog system, which provides the required interoperability and customisation. We showcase the LPaaS potential through a case study designed as a simplification of the motivating scenarios.
Privacy through Anonymisation in Large-scale Socio-technical Systems: The BIS...Andrea Omicini
Large-scale socio-technical systems (STS) inextricably inter-connect individual – e.g., the right to privacy –, social – e.g., the effectiveness of organisational processes –, and technology issues —e.g., the software engineering process. As a result, the design of the complex software infrastructure involves also non-technological aspects such as the legal ones—so that, e.g., law-abidingness can be ensured since the early stages of the software engineering process. By focussing on contact centres (CC) as relevant examples of knowledge-intensive STS, we elaborate on the articulate aspects of anonymisation: there, individual and organisational needs clash, so that only an accurate balancing between legal and technical aspects could possibly ensure the system efficiency while preserving the individual right to privacy. We discuss first the overall legal framework, then the general theme of anonymisation in CC. Finally we overview the technical process developed in the context of the BISON project.
Project presentation @ DMI, Università di Catania, Italy, 25 July 2016
The impact of mobile technologies on healthcare is particularly evident in the case of self-management of chronic diseases, where they can decrease spending and improve the patient quality of life. In this talk we propose the adoption of agent-based modelling and simulation techniques as built-in tools to dynamically monitor patient health state and provide feedbacks for self-management. To demonstrate the feasibility of our proposal we focus on Type 1 Diabetes Mellitus as our case study, and provide some preliminary simulation results.
Game Engines to Model MAS: A Research RoadmapAndrea Omicini
Game engines are gaining increasing popularity in various computational research areas, and in particular in the context of Multi-Agent Systems (MAS)—for instance, to render augmented reality environments, improve immersive simulation infrastructures, and so on. Existing examples of successful integration between game engines and MAS still focus on specific technology-level goals, rather than on shaping a general-purpose game-based agent-oriented infrastructure. In this roadmap talk, we point out the conceptual issues to be faced to exploit game engines as agent-oriented infrastructures, and outline a possible research roadmap to follow, backed up by some early experiments involving the Unity3D engine.
Open distributed multi-agent systems featuring autonomous components demand coordination mechanisms for both functional and non-functional properties. Heterogeneity of requirements regarding interaction means and paradigms, stemming from the diverse nature of components, should not affect the effectiveness of coordination. Along this line, in this paper we share our pragmatical experience in the integration of objective and subjective, synchronous and asynchronous, reactive and pro-active coordination approaches within two widely-adopted agent-oriented technologies (JADE and Jason), enabling coordinating components to dynamically adapt their interaction means based on static preference or run-time contingencies.
Towards Logic Programming as a Service: Experiments in tuPrologAndrea Omicini
In this talk we explore the perspective of Logic Programming as a Service (LPaaS), with a broad notion of “service” going beyond the mere handling of the logic engine lifecycle, knowledge base management, reasoning queries execution, etc. In particular, we present tuProlog as-a-service, a Prolog engine based on the tuProlog core made available as an encapsulated service to effectively support the spreading of intelligence in pervasive systems—mainly, Internet-of-Things (IoT) applications scenarios. So, after recalling the main features of tuProlog technology, we discuss the design and implementation of tuProlog as-a-service, focussing in particular on the iOS platform because of the many supported smart devices (phones, watches, etc.), the URL-based communication support among apps, and the multi-language resulting scenarios.
The huge availability of geographical and spatial data, along with the impulse from ubiquitous and pervasive application scenarios, has pushed the boundaries of complex system engineering towards spatial computing. There, space (in any of the many possible acceptations of the term) represents at the same time the physical container of distributed pervasive applications, the source of a huge amount of data, information, and knowledge, and the target of both epistemic and practical actions.
Agents – as the basic abstraction for distributed computing –, rational agents – as the basic units for encapsulating intelligence –, and multi-agent systems (MAS) – as the social abstraction for collective behaviours – represent the most likely candidates for providing an original framework for spatial computing coherehtly covering conceptual, technical, and methodological issues.
In this survey tutorial we elaborate on the state-of-the art of spatial computing, and show how the classical ontological foundation for MAS (agents, societies, and environment) can coherently capture the essential aspects of spatial computing, also providing for original perspectives and research directions in the novel field of "Spatial MAS".
Academic Publishing in the Digital Era: A Couple of Issues (Open Access—Well,...Andrea Omicini
Open Access is the new frontier for academic publishing: however, some non-trivial issues are yet to be addressed.
Meeting “The (r)evolution of academic publication”
Istituti di Studi Avanzati (ISA), Università di Bologna, Italy, 10/05/2016
Self-organisation of Knowledge in Socio-technical Systems: A Coordination Per...Andrea Omicini
Some of the most peculiar traits of socio-technical systems (STS) in knowledge-intensive environments (KIE) – such as unpredictability of agents’ behaviour, ever-growing amount of information to manage, fast-paced production/consumption – tangle coordination of agents as well as coordination of information, by affecting, e.g., reachability by knowledge prosumers and manageability by the IT infrastructure. In this seminar we describe a novel approach to coordination of STS in KIE, grounded on the MoK (Molecules of Knowledge) model for knowledge self-organisation, and inspired to key concepts from the cognitive theory of BIC (behavioural implicit communication).
Anticipatory Coordination in Socio-technical Knowledge-intensive Environments...Andrea Omicini
ome of the most peculiar traits of socio-technical KIE (knowledge-intensive environments) -- such as unpredictability of agents' behaviour, ever-growing amount of information to manage, fast-paced production/consumption -- tangle coordination of information, by affecting, e.g., reachability by knowledge prosumers and manageability by the IT infrastructure.
Here, we propose a novel approach to coordination in KIE, by extending the MoK model for knowledge self-organisation with key concepts from the cognitive theory of BIC (behavioural implicit communication).
Blending Event-Based and Multi-Agent Systems around Coordination AbstractionsAndrea Omicini
While event-based architectural style has become prevalent for large-scale distributed applications, multi-agent systems seemingly provide the most viable abstractions to deal with complex distributed systems. In this talk we discuss the role of coordination abstractions as a basic brick for a unifying conceptual framework for agent-based and event-based systems, which could work as the foundation of a principled discipline for the engineering of complex software systems.
[Talk by Stefano Mariani @ COORDINATION 2015, 3/6/3015, Grenoble, France]
Event-Based vs. Multi-Agent Systems: Towards a Unified Conceptual FrameworkAndrea Omicini
Event-based systems (EBS) are nowadays the most viable sources of technologies and solutions for large-scale distributed applications. On the other hand, multi-agent systems (MAS) apparently provide the most viable abstractions and coherent methods to deal with complex distributed systems, in particular when advanced features – such as mobility, autonomy, symbolic reasoning, knowledge management, situation recognition – are required. In this talk we discuss how the core concepts of EBS and MAS can in principle be matched and integrated, providing a sound conceptual ground for a coherent discipline for the engineering of complex software systems.
[Keynote Speech @ IEEE CSCWD 2015, May 6, 2015, Calabria, Italy]
Stochastic Coordination in CAS: Expressiveness & PredictabilityAndrea Omicini
Recognising that (i) coordination is a fundamental concern when both analysing and modelling CAS, and that (ii) CAS often exhibit stochastic behaviours, stemming from probabilistic and time-dependent local (interaction) mechanisms, in this talk we argue that (a) measuring expressiveness of coordination languages, and (b) predicting behaviours of stochastic systems based on coordination models are two fundamental steps in the quest for designing well- engineered CAS.
As a concrete ground where to or discussion, we describe some of our current works as well as our ideas for further research.
[with Stefano Mariani @ Dagstuhl Seminar “CAS: Qualitative and Quantitative Modelling and Analysis”, December 14-19th, 2014
TuCSoN Coordination for MAS Situatedness: Towards a MethodologyAndrea Omicini
Agent-based technologies embed solutions for critical issues in agent-oriented software engineering. In this paper we describe the coordination-based approach to MAS situatedness as promoted by the TuCSoN middleware, by sketching the steps of an agent-oriented methodology from the TuCSoN meta-model down to the TuCSoN programming environment.
Event-Based vs. Multi-Agent Systems: Towards a Unified Conceptual Framework. ...Andrea Omicini
Multi-Agent Systems (MAS) and Event-Based Systems (EBS) are two fundamental paradigms for the engineering of complex software systems. In this talk, we summarise the most important features of the MAS and EBS, and discuss how they could be integrated within a unified conceptual framework. The resulting framework could work as the foundation of a principled discipline for the engineering of complex software systems, by promoting a coherent integration of agent-based and event-based abstractions, languages, technologies, and methods.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...
Complexity in computational systems: the coordination perspective
1. Complexity in Computational Systems:
The Coordination Perspective
Andrea Omicini
andrea.omicini@unibo.it
Dipartimento di Informatica – Scienza e Ingegneria (DISI)
Alma Mater Studiorum – Universit`a di Bologna a Cesena
Complex Systems Physics / IMT-UniBo
Bologna, Italy, 15 February 2018
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 1 / 45
2. Outline
1 Complexity & Computer Science
2 Interaction & Coordination
3 Interacting Systems
4 A Case Study: Socio-technical Systems
5 Final Remarks
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 2 / 45
3. Complexity & Computer Science
Next in Line. . .
1 Complexity & Computer Science
2 Interaction & Coordination
3 Interacting Systems
4 A Case Study: Socio-technical Systems
5 Final Remarks
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 3 / 45
4. Complexity & Computer Science
Modelling vs. Building Complex Systems
Everybody knows that. . .
the notion of complexity is definitely a multi-disciplinary one, ranging
from physics to biology, from economics to sociology and organisation
sciences
systems that are said complex are both natural and artificial ones
Physical vs. computational complex systems
as they are natural systems, we observe and model complex physical
systems
as they are artificial systems, we design and build complex
computational systems
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 4 / 45
5. Complexity & Computer Science
Complexity in Computational Systems I
A “simple” notion of complexity to start with
. . . by a complex system I mean one made up of a large number
of parts that interact in a non simple way [Simon, 1962]
. . . towards interaction
if some “laws of complexity” exists that characterise any complex
system, independently of its specific nature [Kauffman, 2003]
we focus on interaction – its nature, structure, dynamics – as the key
to understand some fundamental properties of complex systems
in particular complex computational systems
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 5 / 45
6. Complexity & Computer Science
Complexity in Computational Systems II
An essential source of complexity for computational systems is
interaction
[Goldin et al., 2006]
The power of interaction [Wegner, 1997]
Interaction is a more powerful paradigm than rule-based algorithms
for computer-based solving, overtiring the prevailing view that all
computing is expressible as algorithms.
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 6 / 45
7. Complexity & Computer Science
Complexity in Computational Systems III
Intelligence & interaction [Brooks, 1991]
Real computational systems are not rational agents that take in-
puts, compute logically, and produce outputs. . . It is hard to draw
the line at what is intelligence and what is environmental interac-
tion. In a sense, it does not really matter which is which, as all
intelligent systems must be situated in some world or other if they
are to be useful entities.
A conceptual framework for interaction [Milner, 1993]
. . . a theory of concurrency and interaction requires a new con-
ceptual framework, not just a refinement of what we find natural
for sequential [algorithmic] computing.
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 7 / 45
8. Complexity & Computer Science
Interaction & Expressiveness I
Interactive computing [Wegner and Goldin, 1999]
finite computing agents that interact with an environment are shown
to be more expressive than Turing machines according to a notion of
expressiveness that measures problem-solving ability and is specified
by observation equivalence
sequential interactive models of objects, agents, and embedded
systems are shown to be more expressive than algorithms
multi-agent (distributed) models of coordination, collaboration, and
true concurrency are shown to be more expressive than sequential
models
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 8 / 45
9. Complexity & Computer Science
Interaction & Expressiveness II
Basically, where does complexity come from?
events in a sequential component are totally ordered
as soon as we combine components in a concurrent system
(distribution in time), they are no longer totally ordered
as soon as we combine components in a distributed system
(distribution in space), interaction occurs in different contexts
interaction make the overall system essentially unpredictable
! the range of behaviours that an interactive system can exhibit is
typically larger than non-interactive systems
→ more behaviours means more expressiveness
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 9 / 45
10. Complexity & Computer Science
Building Complex Computational Systems I
Interaction as a computational dimension
interaction as a fundamental dimension for modelling and engineering
complex computational systems
for instance, a well-founded theory of interaction is essential to model
sociality [Castelfranchi et al., 1993] and situatedness [Mariani and Omicini, 2015]
in multi-agent systems (MAS)
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 10 / 45
11. Complexity & Computer Science
Building Complex Computational Systems II
Compositionality, formalisability, expressiveness
roughly speaking, when interaction within a system is (not) relevant,
system properties cannot (can) be straightforwardly derived by
component properties
compositional vs. non-compositional systems
computer scientists vs. computer engineers
system formalisability vs. system expressiveness
e.g., interaction is the main source of emergent social phenomena in MAS
[Castelfranchi, 1998]
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 11 / 45
12. Complexity & Computer Science
Building Complex Computational Systems III
Interaction as a first-class issue
The inter-disciplinary study of interaction in many diverse scientific areas dealing
with complex systems basically draws the foremost lines of evolution of
contemporary computational systems [Omicini et al., 2006]
interaction — an essential and independent dimension of computational systems,
orthogonal to mere computation
[Gelernter and Carriero, 1992, Wegner, 1997]
environment — a first-class abstraction in the modelling and engineering of complex
computational systems, such as pervasive, adaptive, and multi-agent
systems [Weyns et al., 2007]
mediation — environment-based mediation [Ricci and Viroli, 2005] is the key to
designing and shaping the interaction space within complex software
systems, in particular socio-technical ones [Omicini, 2012]
middleware — provides complex socio-technical systems with the mediating
abstractions required to rule and govern social and environment
interaction [Viroli et al., 2007]
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 12 / 45
13. Interaction & Coordination
Next in Line. . .
1 Complexity & Computer Science
2 Interaction & Coordination
3 Interacting Systems
4 A Case Study: Socio-technical Systems
5 Final Remarks
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 13 / 45
14. Interaction & Coordination
Harnessing the Complexity of Interaction
coordination is managing interaction [Wegner, 1997]
coordination models work by constraining the space of interaction
[Wegner, 1996]
so, in principle, coordination abstractions and technologies can help
harnessing the intricacies of interaction in the engineering of complex
software systems
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 14 / 45
15. Interaction & Coordination
A Meta-model for Coordinated Systems I
The coordination meta-model [Ciancarini, 1996]
coordination entities — the entities whose mutual interaction is ruled by
the model, also called the coordinables (or, the agents)
coordination media — the abstractions enabling and ruling interaction
among coordinables
coordination laws — the rules governing the observable behaviour of
coordination media and coordinables, and their interaction as
well
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 15 / 45
16. Interaction & Coordination
A Meta-model for Coordinated Systems II
interaction space
coordinable
coordination
medium
coordinable
coordinable
coordination
medium
coordination
medium
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 16 / 45
17. Interaction & Coordination
A Meta-model for Coordinated Systems III
The coordination media. . .
“fill” the interaction space
enable / promote / govern the admissible / desirable / required
interactions among the interacting entities
according to some coordination laws
enacted by the behaviour of the media
defining the semantics of coordination
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 17 / 45
18. Interaction & Coordination
A New Perspective over Computational Systems
Programming languages
interaction as an orthogonal dimension
languages for interaction / coordination
Software engineering
interaction as an independent design dimension
coordination patterns
Artificial intelligence
interaction as a new source for intelligence
social intelligence
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 18 / 45
19. Interacting Systems
Next in Line. . .
1 Complexity & Computer Science
2 Interaction & Coordination
3 Interacting Systems
4 A Case Study: Socio-technical Systems
5 Final Remarks
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 19 / 45
20. Interacting Systems
Interaction in Physical Systems I
Independence from interaction
some physical systems are described under the assumption of mutual
independence among particles—that is, the behaviour of the particles
is unaffected by their mutual interaction
e.g., ideal gas [Boltzmann, 1964]
there, the probability distribution of the whole system is the product of
those of each of its particles
in computer science terms, the properties of the system can be
compositionally derived by the properties of the individual
components [Wegner, 1997]
→ neither macroscopic sudden shift nor abrupt change for the system as
a whole: technically, those systems have no phase transitions—of
course, while the “independence from interaction” hypothesis holds
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 20 / 45
21. Interacting Systems
Interaction in Physical Systems II
Interacting systems
introducing interaction among particles structurally changes the
macroscopic properties, along with the mathematical ones
interacting systems are systems where particles do not behave
independently of each other
the probability distribution of an interacting system does not factorise
anymore
in computer science terms, an interacting system is non-compositional
[Wegner, 1997]
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 21 / 45
22. Interacting Systems
From Physical to Social Systems I
Large numbers
key point in statistical mechanics is to relate the macroscopic
observables quantities – like pressure, temperature, etc. – to suitable
averages of microscopic observables—like particle speed, kinetic
energy, etc.
based on the laws of large numbers, the method works for those
systems made of a large number of particles / basic components
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 22 / 45
23. Interacting Systems
From Physical to Social Systems II
Beyond the boundaries
methods for complex systems from statistical mechanics have
expanded from physics to fields as diverse as biology [Kauffman, 1993],
economics [Bouchaud and Potters, 2003, Mantegna and Stanley, 1999], and
computer science itself [M´ezard and Montanari, 2009, Nishimori, 2001]
recently, they have been applied to social sciences as well: there is
evidence that the complex behaviour of many observed
socio-economic systems can be approached with the quantitative
tools from statistical mechanics
e.g., econophysics for crisis events [Stanley, 2008]
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 23 / 45
24. Interacting Systems
From Physical to Social Systems III
Social systems as interacting systems
a group of isolated individuals neither knowing nor communicating
with each other is the typical example of a compositional social
system
no sudden shifts are expected in this case at the collective level,
unless it is caused by strong external exogenous causes
to obtain a collective behaviour displaying endogenous phenomena,
the individual agents should meaningfully interact with each other
the foremost issue here is that the nature of the interaction determines
the nature of the collective behaviour at the aggregate level
e.g., a simple imitative interaction is capable to cause strong
polarisation effects even in presence of extremely small external inputs
(non-trivial) social systems as interacting systems
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 24 / 45
25. Interacting Systems
Coordinated Systems as Interacting Systems I
Coordination media for ruling interaction
defining the abstractions for ruling the interaction space in
computational systems basically means to define their coordination
model [Gelernter and Carriero, 1992, Ciancarini, 1996, Ciancarini et al., 1999]
global properties of complex coordinated systems depending on
interaction can be enforced through the coordination model,
essentially based on its expressiveness [Zavattaro, 1998, Denti et al., 1998]
for instance, tuple-based coordination models have been shown to be
expressive enough to support self-organising coordination patterns for
nature-inspired distributed systems [Omicini, 2013]
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 25 / 45
26. Interacting Systems
Coordinated Systems as Interacting Systems II
The role of coordination models
Coordination models could be exploited
to rule the interaction space
so as to define new sorts of global, macroscopic properties for
computational systems—possibly inspired by physical ones
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 26 / 45
27. Interacting Systems
Coordinated Systems as Interacting Systems III
Research perspectives
We need to understand
how to relate methods from physics with coordination models
whether physics notions such as phase, phase transition, or any other
macroscopic system property could translate from statistical
mechanics to computer science
what such notions would imply for computational systems
whether new, original notions could apply to computational systems
which sort of coordination model could support such notions
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 27 / 45
28. A Case Study: Socio-technical Systems
Next in Line. . .
1 Complexity & Computer Science
2 Interaction & Coordination
3 Interacting Systems
4 A Case Study: Socio-technical Systems
5 Final Remarks
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 28 / 45
29. A Case Study: Socio-technical Systems
Socio-Technical Systems
Humans vs. software
nowadays, a particularly-relevant class of social systems is represented
by socio-technical systems (STS) [Whitworth, 2006]
in STS
active components are mainly represented by humans
whereas interaction is almost-totally regulated by the software
infrastructure
where software agents often play a key role
this is the case, for instance, of social platforms like FaceBook
[FaceBook, 2013] and LiquidFeedback [LiquidFeedback, 2013]
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 29 / 45
30. A Case Study: Socio-technical Systems
Physical & Computational Social Systems I
A twofold view of socio-technical systems
the nature of STS is twofold: they are both social systems and
computational systems [Verhagen et al., 2013, Omicini, 2012]
as complex social systems, their complex behaviour is in principle
amenable of mathematical modelling and prediction through notions
and tools from statistical mechanics
as complex computational systems, they are designed and built
around some (either implicit or explicit) notion of coordination, ruling
the interaction within components of any sort—be them either
software or human ones
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 30 / 45
31. A Case Study: Socio-technical Systems
Physical & Computational Social Systems II
Computational systems meet physical systems
in STS, macroscopic properties could be
described by exploiting the conceptual tools from physics
enforced by the coordination abstractions
STS could exploit both
the notion of complexity by statistical mechanics, along with the
mathematical tools for behaviour modelling and prediction, and
coordination models and languages to suitably shape the interaction
space
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 31 / 45
32. A Case Study: Socio-technical Systems
Physical & Computational Social Systems III
Vision
Complex socio-technical systems could be envisioned
whose implementation is based on suitable coordination models
whose macroscopic properties can be modelled and predicted by
means of mathematical tools from statistical physics
thus reconciling the scientist and the engineer views over systems
First reading
paper [Omicini and Contucci, 2013]
presentation http://www.slideshare.net/andreaomicini/complexity-interaction-
blurring-borders-between-physical-computational-and-social-
systems-preliminary-notes
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 32 / 45
33. Final Remarks
Next in Line. . .
1 Complexity & Computer Science
2 Interaction & Coordination
3 Interacting Systems
4 A Case Study: Socio-technical Systems
5 Final Remarks
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 33 / 45
34. Final Remarks
Conclusion I
Interaction in complex systems
Interaction is key issue for complex systems
interacting systems in physics
coordinated systems in computer science
socio-technical systems such as social platforms
e.g., FaceBook, LiquidFeedback
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 34 / 45
35. Final Remarks
Conclusion II
The role of coordination models
coordinated systems as interacting systems
coordination models as the sources of abstractions and technology for
enforcing global properties in complex computational systems, which
could then be
modelled as physical systems, and
engineered as computational systems
Case study
Socio-technical systems such as large social platforms could represent a
perfect case study for the convergence of the ideas and tools from
statistical mechanics and computer science, being both social and
computational systems at the same time
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 35 / 45
36. Final Remarks
Conclusion III
Next steps
We are currently experimenting with digital democracy platforms by
exploiting
coordination technologies for setting macroscopic system properties
statistical mechanics tools for predicting global system behaviour
Andrea Omicini (DISI, Univ. Bologna) Complexity & Coordination 15/2/2018 36 / 45
37. References
References I
Boltzmann, L. (1964).
Lectures on Gas Theory.
University of California Press.
Bouchaud, J.-P. and Potters, M. (2003).
Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk
Management.
Cambridge University Press, Cambridge, UK, 2nd edition.
Brooks, R. A. (1991).
Intelligence without reason.
In Mylopoulos, J. and Reiter, R., editors, 12th International Joint Conference on Artificial
Intelligence (IJCAI 1991), volume 1, pages 569–595, San Francisco, CA, USA. Morgan
Kaufmann Publishers Inc.
Castelfranchi, C. (1998).
Modelling social action for AI agents.
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45. Complexity in Computational Systems:
The Coordination Perspective
Andrea Omicini
andrea.omicini@unibo.it
Dipartimento di Informatica – Scienza e Ingegneria (DISI)
Alma Mater Studiorum – Universit`a di Bologna a Cesena
Complex Systems Physics / IMT-UniBo
Bologna, Italy, 15 February 2018
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