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Anticipatory Coordination in Socio-technical Knowledge-intensive Environments: Behavioural Implicit Communication in MoK

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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).

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Anticipatory Coordination in Socio-technical Knowledge-intensive Environments: Behavioural Implicit Communication in MoK

  1. 1. Anticipatory Coordination in Socio-technical Knowledge-intensive Environments: Behavioural Implicit Communication in MoK Stefano Mariani, Andrea Omicini Alma Mater Studiorum—Universit`a di Bologna, Italy AIxIA 2015 Ferrara, Italy 24th September 2015 Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 1 / 31
  2. 2. Outline 1 Premises 2 Ingredients 3 Towards Anticipatory Coordination 4 Experiment 5 Conclusion Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 2 / 31
  3. 3. Premises Outline 1 Premises 2 Ingredients 3 Towards Anticipatory Coordination 4 Experiment 5 Conclusion Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 3 / 31
  4. 4. Premises Challenges of Socio-technical Systems Socio-technical systems (STS) arise when cognitive and social interaction is mediated by information technology, rather than by the natural world (alone) [Whi06] STS are heavily interaction-centred, so they need coordination at the infrastructure level [MC94] Coordination issues in STS are: unpredictability “humans-in-the-loop”, whereas software behaviour is programmable and predictable, human’s is not scale physically-distributed, open systems, large-scale, ever-increasing number of people, devices, data Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 4 / 31
  5. 5. Premises Challenges of Knowledge-intensive Environments Knowledge-intensive Environments (KIE) are workplaces in which sustainability of the organisation long-term goals is influenced by the evolution of knowledge [Bha01] Usually, KIE are computationally supported by STS, so they need coordination too Coordination issues in KIE are: size massive amount of raw data, aggregated information, reification of procedures and best-practices, and the like pace data is produced and consumed at a fast pace, huge frequency of interactions Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 5 / 31
  6. 6. Premises The Idea Coordination models and technologies draw inspiration from distributed collective intelligence phenomena in natural systems, looking for self-organising and adaptive coordination mechanisms [VPB12, MZ09, VC09, ZCF+11, MO13] A novel perspective Similarly, we focus the “social layer” of STS, looking for novel coordination approaches inspired by the latest cognitive and social sciences theories of action. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 6 / 31
  7. 7. Premises The Approach 1 We take as a reference the M olecules of K nowledge (MoK ) coordination model for knowledge self-organisation in KIE [MO13] 2 Extend it toward the notion of anticipatory coordination — as a form of collective intelligence arising by emergence 3 According to the theory of Behavioural Implicit Communication (BIC) [CPT10] Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 7 / 31
  8. 8. Ingredients Outline 1 Premises 2 Ingredients 3 Towards Anticipatory Coordination 4 Experiment 5 Conclusion Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 8 / 31
  9. 9. Ingredients Behavioural Implicit Communication Implicit interaction Behavioural implicit communication (BIC) is a form of implicit interaction with no specialised signal conveying the message, since the message is the practical behaviour itself — and possibly, its traces [CPT10]. BIC presupposes observation: agents should be able to observe others’ actions (and traces), as well as to mind-read the intentions behind them BIC applies to human beings, to both cognitive and non-cognitive agents, and to computational environments as well [WOO07] Smart environments are pro-active, intelligent working environments able to autonomously adapt their behaviour according to users’ interactions [CPT10] 1 1 Which is, not by chance, the very notion of anticipatory coordination. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 9 / 31
  10. 10. Ingredients Smart (Computational) Environments In [TCR+05], an abstract model for smart environments defines two types of environment: c-env common environment, where agents can observe only the state of the environment (including actions’ traces), not the actions of their peers s-env shared environment, enabling different forms of observability of actions, and awareness of this observability Three requirements can thus be devised: 1 observability of agents’ actions and traces enabled by default 2 the environment should be able to understand actions and their traces, possibly inferring intentions and goals motivating them 3 agents should be able to understand the effects of their activity on both the environment and other agents, so as to opportunistically obtain a reaction Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 10 / 31
  11. 11. Ingredients M olecules of K nowledge I MoK M olecules of K nowledge (MoK ) is a coordination model promoting self-organisation of knowledge [MO13]. Inspired to biochemical tuple spaces [VC09] and stigmergic coordination [Par06] Main goals: 1 self-aggregation of information into more complex heaps, possibly reifying useful knowledge previously hidden 2 autonomous diffusion of information toward the interested agents, that is, those needing it to achieve their goals Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 11 / 31
  12. 12. Ingredients M olecules of K nowledge II A MoK -coordinated system is thus: a network of MoK compartments (tuple-space like information repositories) in which MoK seeds (sources of information) autonomously inject MoK atoms (information pieces) atoms undergo autonomous and decentralised reactions aggregate into molecules (composite information chunks) diffuse to neighbourhoods gets reinforced and perturbed by users decay as time flows reactions are influenced by enzymes (reification of users’ epistemic actions) and scheduled according to Gillespie’s chemical dynamics simulation algorithm [Gil77] Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 12 / 31
  13. 13. Towards Anticipatory Coordination Outline 1 Premises 2 Ingredients 3 Towards Anticipatory Coordination 4 Experiment 5 Conclusion Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 13 / 31
  14. 14. Towards Anticipatory Coordination MoK Compartments as c-env The only sort of smart environment enabled in MoK is c-env, mapped upon a compartment, because [MO13]: 1 no sharing of compartments is assumed 2 enzymes are visible only to MoK reactions 3 enzymes cannot diffuse, thus neighbourhoods cannot perceive them So, MoK does not support s-env since there is no observable action reification in shared environments Also, support to c-env is limited to compartments – not neighbourhoods – since enzymes cannot diffuse Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 14 / 31
  15. 15. Towards Anticipatory Coordination MoK Compartments as s-env Compartment can now be shared among users Enzymes are diversified to resemble the epistemic nature of the action they reify made observable to users sharing the compartment they live in no longer consumed by reinforcement reaction, but now subject to decay now generating traces through a deposit reaction Traces are introduced as the MoK abstraction resembling (side) effects of actions different in kind, according to their “father” enzyme observable solely by MoK reactions subject to diffusion, decay and to a novel enzyme-dependant perturbation reaction MoK compartments extension leads to neighbourhoods representing c-env, where action traces may diffuse, becoming part of the environment as they participate MoK reactions Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 15 / 31
  16. 16. Towards Anticipatory Coordination Enzymes and Traces as BIC Enablers I Model enzyme(species, s, mol)c enzyme(species, s, mol ) + molc rreinf −−−→ enzyme(species, s, mol ) + molc+s trace(enzyme, p, mol)c trace(enzyme, p, mol ) + molc rpert −−→ .exec (p, trace, mol) enzyme rdep −−→ enzyme + trace(enzyme, p[species], mol) species defines the epistemic nature of the action s strength of reinforcement p the perturbation the trace wants to perform .exec starts execution of perturbation p 2 Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 16 / 31
  17. 17. Towards Anticipatory Coordination Enzymes and Traces as BIC Enablers II Reinforcement influences relevance of information according to the (epistemic) nature and frequency of their actions, so as to better support them in pursuing their goals Enzymes situate actions, e.g., at a precise time as well as in a precise space Mind-reading and signification by assuming that users manipulating a given corpus of information are interested in that information more than other Perturbation influences location, content, any domain-specific trait of information, according to users’ inferred goals, with the goal of easing and optimising their workflows Traces enable the environment to exploit users’ actions (possibly, inferred) side-effects for the profit of the coordination process — promoting the distributed collective intelligence leading to anticipatory coordination 2 Notice, p is implicitly defined by species, as highlighted by notation p[species]. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 17 / 31
  18. 18. Towards Anticipatory Coordination Tacit Messages Steering Anticipatory Coordination I Tacit messages [CPT10] describe the kind of messages a practical action (and its traces) may implicitly send to its observers: presence “Agent X is here”. Since an action (trace) is observable in shared compartments (neighbourhoods), any agent therein becomes aware of X existence and location — likewise for the environment. intention “X plans to do action b”. If the agents’ workflow determines that action b follows action a, peers (as well as the environment) observing X doing a may assume X next intention to be “do b”. Accordingly, the environment may decide to undertake anticipatory coordination actions easing/hindering action b — e.g. because action b is computationally expensive. ability “X is able to do ai=1,...,n” . . . . . . Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 18 / 31
  19. 19. Towards Anticipatory Coordination Tacit Messages Steering Anticipatory Coordination II . . . . . . opportunity “ [e1, . . . , en] is the set of pre-conditions for doing a” accomplishment “X achieved S” goal “X has goal g” result “Result r is available” Enabling Collective Intelligence Since agents can undertake the above described inferences, MoK compartments actually act as BIC-based enablers of distributed collective intelligence phenomena — e.g., anticipatory coordination emerging due to agent interaction. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 19 / 31
  20. 20. Towards Anticipatory Coordination Tacit Messages Steering Anticipatory Coordination III In many STS, a set of fairly-common actions may be devised, in spite of the diversity in scope of the software platforms — e.g. Facebook vs. Mendeley: quote/share re-publishing or mentioning someone else’s information can convey, e.g., tacit messages presence, ability, accomplishment. If X shares Y ’s information through action a, every other agent observing a becomes aware of existence and location of both X and Y (1). The fact that X is sharing information I from source S lets X’s peers infer X can manipulate S (3). If X shared I with Z, Z may infer, e.g., that X expects Z to somehow use it (5). like/favourite marking as relevant a piece of information can convey, e.g., tacit messages presence, opportunity. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 20 / 31
  21. 21. Towards Anticipatory Coordination Tacit Messages Steering Anticipatory Coordination IV follow subscribing for updates regarding some piece of information or some user can convey tacit messages intention, opportunity. search performing a search query to retrieve information can convey, e.g., tacit messages presence, intention, opportunity. Perturbation Actions Accordingly, each tacit message may cause a perturbation action contributing to anticipatory coordination — e.g. send discovery messages, establish privileged communication channels, undertake coordination actions enabling/forbidding some interaction protocol, notify users about availability of novel information, etc. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 21 / 31
  22. 22. Experiment Outline 1 Premises 2 Ingredients 3 Towards Anticipatory Coordination 4 Experiment 5 Conclusion Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 22 / 31
  23. 23. Experiment Simulated Scenario Citizen journalism scenario 3 users share a MoK -coordinated IT platform for retrieving and publishing news stories users have personal devices (smartphones, tablets, pcs, workstations), running the MoK middleware, which they use to search the IT platform for relevant information search actions can spread up to a neighbourhood of compartments — e.g., to limit bandwidth consumption, boost security, optimise information location, etc. search actions leave traces the MoK middleware exploits to attract similar information, actually enacting anticipatory coordination 3 Technical details of the simulations – e.g. tools used and simulation parameters – in the full paper. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 23 / 31
  24. 24. Experiment Self-organising Adaptive Anticipatory Coordination Figure: Whereas data is initially randomly scattered across workspaces, as soon as users interact clusters appear by emergence thanks to BIC-driven self-organisation. Whenever new actions are performed by catalysts, the MoK infrastructure adaptively re-organises the spatial configuration of molecules so as to better tackle the new coordination needs. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 24 / 31
  25. 25. Conclusion Outline 1 Premises 2 Ingredients 3 Towards Anticipatory Coordination 4 Experiment 5 Conclusion Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 25 / 31
  26. 26. Conclusion Conclusion & Outlook Although our experiment focusses on one specific pattern of anticipatory coordination, results are more than encouraging, deserving further investigation Efforts are currently devoted to fully implement and run a MoK coordinated system on a large-scale scenario—a prototype implementation of MoK exists, but large-scale deployment has not been achieved, yet Special care will be payed to the semantic similarity measure ontology-based semantic matching is rather unfeasible in pervasive, mobile scenarios purely syntactical matching has too low expressiveness viable tradeoffs may be usage of wildcards, e.g. as in Java regular expressions4 , or of synonymy relationships, e.g. as done in [PVM+ 10] using WordNet5 4 http://docs.oracle.com/javase/tutorial/essential/regex/ 5 http://wordnet.princeton.edu Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 26 / 31
  27. 27. References References I Ganesh D. Bhatt. Knowledge management in organizations: Examining the interaction between technologies, techniques, and people. Journal of Knowledge Management, 5(1):68–75, 2001. Cristiano Castelfranchi, Giovanni Pezzullo, and Luca Tummolini. Behavioral implicit communication (BIC): Communicating with smart environments via our practical behavior and its traces. International Journal of Ambient Computing and Intelligence, 2(1):1–12, January–March 2010. Daniel T. Gillespie. Exact stochastic simulation of coupled chemical reactions. The Journal of Physical Chemistry, 81(25):2340–2361, December 1977. Thomas W. Malone and Kevin Crowston. The interdisciplinary study of coordination. ACM Computing Surveys, 26(1):87–119, 1994. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 27 / 31
  28. 28. References References II Stefano Mariani and Andrea Omicini. Molecules of Knowledge: Self-organisation in knowledge-intensive environments. In Giancarlo Fortino, Costin B˘adic˘a, Michele Malgeri, and Rainer Unland, editors, Intelligent Distributed Computing VI, volume 446 of Studies in Computational Intelligence, pages 17–22. Springer, 2013. Marco Mamei and Franco Zambonelli. Programming pervasive and mobile computing applications: The TOTA approach. ACM Transactions on Software Engineering and Methodology (TOSEM), 18(4), July 2009. H. Van Dyke Parunak. A survey of environments and mechanisms for human-human stigmergy. In Danny Weyns, H. Van Dyke Parunak, and Fabien Michel, editors, Environments for Multi-Agent Systems II, volume 3830 of Lecture Notes in Computer Science, pages 163–186. Springer, 2006. Danilo Pianini, Sascia Virruso, Ronaldo Menezes, Andrea Omicini, and Mirko Viroli. Self organization in coordination systems using a WordNet-based ontology. In Indranil Gupta, Salima Hassas, and Rolia Jerome, editors, 4th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2010), pages 114–123, Budapest, Hungary, 27 September–1 October 2010. IEEE CS. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 28 / 31
  29. 29. References References III Luca Tummolini, Cristiano Castelfranchi, Alessandro Ricci, Mirko Viroli, and Andrea Omicini. “Exhibitionists” and “voyeurs” do it better: A shared environment approach for flexible coordination with tacit messages. In Danny Weyns, H. Van Dyke Parunak, and Fabien Michel, editors, Environments for Multi-Agent Systems, volume 3374 of Lecture Notes in Artificial Intelligence, pages 215–231. Springer, February 2005. Mirko Viroli and Matteo Casadei. Biochemical tuple spaces for self-organising coordination. In John Field and Vasco T. Vasconcelos, editors, Coordination Languages and Models, volume 5521 of Lecture Notes in Computer Science, pages 143–162. Springer, Lisbon, Portugal, June 2009. Mirko Viroli, Danilo Pianini, and Jacob Beal. Linda in space-time: An adaptive coordination model for mobile ad-hoc environments. In Marjan Sirjani, editor, Coordination Models and Languages, number 7274 in Lecture Notes in Computer Science, pages 212–229. Springer, 2012. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 29 / 31
  30. 30. References References IV Brian Whitworth. Socio-technical systems. Encyclopedia of human computer interaction, pages 533–541, 2006. Danny Weyns, Andrea Omicini, and James J. Odell. Environment as a first-class abstraction in multi-agent systems. Autonomous Agents and Multi-Agent Systems, 14(1):5–30, February 2007. Franco Zambonelli, Gabriella Castelli, Laura Ferrari, Marco Mamei, Alberto Rosi, Giovanna Di Marzo, Matteo Risoldi, Akla-Esso Tchao, Simon Dobson, Graeme Stevenson, Yuan Ye, Elena Nardini, Andrea Omicini, Sara Montagna, Mirko Viroli, Alois Ferscha, Sascha Maschek, and Bernhard Wally. Self-aware pervasive service ecosystems. Procedia Computer Science, 7:197–199, December 2011. Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 30 / 31
  31. 31. Anticipatory Coordination in Socio-technical Knowledge-intensive Environments: Behavioural Implicit Communication in MoK Stefano Mariani, Andrea Omicini Alma Mater Studiorum—Universit`a di Bologna, Italy AIxIA 2015 Ferrara, Italy 24th September 2015 Mariani, Omicini (Universit`a di Bologna) Anticipatory Coordination: BIC in MoK AIxIA 2015 – 24/9/2015 31 / 31

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