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Intelligent agents the vision revisited


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Intelligent agents the vision revisited

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Intelligent agents the vision revisited

  1. 1. Intelligent Agents: The Vision Revisited Sabrina Kirrane1 and Stefan Decker2 1 Vienna University of Economics and Business 2 RWTH Aachen University
  2. 2. Knowledge Management The Vision!
  3. 3. 3 Memex...1945 “A memex is a device in which an individual stores all his books, records, and communications, and which is mechanized so that it may be consulted with exceeding speed and flexibility” As We May Think, Vannevar Bush, 1945.
  4. 4. “By ‘augmenting human intellect’ we mean increasing the capability of a man to approach a complex problem situation, to gain comprehension to suit his particular needs, and to derive solutions to problems.” Augmenting Human Intellect: A conceptual Framework, Douglas C. Engelbart, 1962. Augmenting human intellect...1962
  5. 5. “This proposal concerns the management of general information about accelerators and experiments at CERN. It discusses the problems of loss of information about complex evolving systems and derives a solution based on a distributed hypertext system.” World Wide Web … 1989 Information Management: A Proposal, Tim Berners-Lee, 1989.
  6. 6. Where do we stand today?
  7. 7. RDF – Resource Description Framework Graph based Data – nodes and arcs –  Identifies objects (IRIs) –  Interlink information (Relationships) Vocabularies (Ontologies) –  provide shared understanding of a domain –  organise knowledge in a machine-comprehensible way –  give an exploitable meaning to the data Knowledge Representation
  8. 8. Images by Hendler, Brickley Novack; The Semantic Web is a stack of technologies for interoperability
  9. 9. Semantic Technology Dynamic aggregations based on a rich ontological domain model. The ontology describes entity existence, groups and relationships between the things/concepts that describe the World Cup. For example, "Frank Lampard" is part of the "England Squad" and the "England Squad" competes in "Group C" of the "FIFA World Cup 2010".
  10. 10. Linked Data The dataset currently contains 1,224 datasets with 16,113 links (as of June 2018)
  11. 11. Open Data The Semantic Web in an Age of Open Data Nigel Shadbolt, ISWC Keynote, 2014
  12. 12. Many applications, especially search engines, can benefit greatly from direct access to structured data. On-page markup enables search engines to understand the information on web pages and provide richer search results.
  13. 13. Existing Challenges •  generally isn’t machine-processable •  can’t be traversed There are still serious barriers to consuming and using LOD
  14. 14. Reflections on the Community “Semantic Web research is changing: It builds on the earlier foundations but it has generated a more diverse set of pursuits” “Representations they used became less formal and precise than many early Semantic Web researchers had envisioned” “Modern semantic approaches leverage vastly distributed, heterogeneous data collection with needs-based, lightweight data integration”
  15. 15. Postulations for the Community •  Representation and lightweight semantics •  Heterogeneity, quality, and provenance •  Latent semantics •  High volume and velocity data
  16. 16. Is Linked Data FAIR? Examining data management through the lens of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles
  17. 17. Is Linked Data FAIR? •  Both Interoperablity and Reusability are at the core of the RDF data model •  HTTP IRIs that can be used to identify things •  Ontologies provide for a shared understanding of things
  18. 18. Is Linked Data FAIR? •  There are several challenges with respect to Findability and Accessibility •  (meta)data should be identifiable via persistent identifiers •  Indexing of (meta)data in a manner that is easy to search •  Usage constraints that describe how the data should be used
  19. 19. Our Position! Towards FAIR ICT Agents whereby ICT denotes Interactive intelligent agents that are Constrained via goals, preferences, norms and usage restrictions, in a manner that fosters Trustworthiness
  20. 20. Interactive Research into decentralized semantic service search is lagging far behind its centralized counterpart •  How do we support adaptive discovery and composition of semantic services? •  How can we enable interoperability between policy aware agents •  Dealing with agents joining and leaving the network at will Apple's 1987 vision of the future Relevant Survey: M. Klusch, P. Kapahnke, S. Schulte, F. Lecue, and A. Bernstein. Semantic web service search: a brief survey. KI-Künstliche Intelligenz , 2016.
  21. 21. Constrained •  A framework that can be used to evaluate existing access control offerings in a federated semantic data management environment •  License aware data querying and processing mechanisms •  Societal norms and personal values that would enable agents to understand the constraints of the environment •  Policy interoperability needs of collaborating agents Relevant Survey: S. Kirrane, A. Mileo, and S. Decker. Access control and the resource description framework: A survey. Semantic Web , 2017.
  22. 22. Trustworthiness •  Validate the effectiveness of existing trust mechanisms in the context of intelligent agents •  Ability to record provenance with respect to both data and processing in a manner that can be easily digestible •  Transparency, governance and accountability •  Dealing with new challenges e.g. algorithmic biases, fake news, filter bubbles Relevant Survey: D. Artz and Y. Gil. A survey of trust in computer science and the semantic web. Web Semantics: Science, Services and Agents on the World Wide Web, 2007.
  23. 23. Closing Remarks! For Intelligent Agents to work in practice Constraints and Trustworthiness need to be built into the foundations of the Semantic Web!