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Agents on the Semantic Web David De Roure Intelligence Agents Multimedia Dept of Electronics and Computer Science University of Southampton, UK

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Presentation on theme: "Agents on the Semantic Web David De Roure Intelligence Agents Multimedia Dept of Electronics and Computer Science University of Southampton, UK"— Presentation transcript:

1 Agents on the Semantic Web David De Roure Intelligence Agents Multimedia Dept of Electronics and Computer Science University of Southampton, UK

2 Semantic Web Technologies November Overview The Pervasive Information Fabric Agents state of play Why agents need metadata Onward to ontologies

3 Semantic Web Technologies November Background This talk is based on the experience of building several applications (research prototypes) involving agents. These include:  Conceptual hypermedia and ontologies  Context-aware hypermedia linking  Information middleware for pervasive computing  Collaborative filtering systems  ‘Content based’ navigation of multimedia (images and music) We have also developed an Agent framework for Distributed Information Management

4 Semantic Web Technologies November Background Current activities include:  Mixed reality adaptive information systems  Advanced knowledge technologies  Disappearing computer initiative project  Simulation of very large scale distributed systems  Grid computing (information/knowledge grid)

5 The Pervasive Information Fabric

6 Semantic Web Technologies November The Web of the past… Is mainly a document dissemination Web Can only link to multimedia Assumes a traditional Web browser Has static hyperstructure

7 Semantic Web Technologies November The Web of the future is… Multimedia, including temporal media Mobile (with different style of working) Adaptive and open e.g. XLink Collaborative Automated (machine-to-machine e.g. XML) Semantic (of course!) And…

8 Semantic Web Technologies November 20008

9 9 …pervasive Embedded internet e.g. The Disappearing Computer Initiative Large numbers of devices Ad hoc networking (some support from IPv6) Systems need to be self organising Don’t wait for 1000s of bluetooth devices before exploring scalability issues! We call the middleware the Pervasive Information Fabric

10 Semantic Web Technologies November …virtual Interface is 3D worlds, telepresence, VR ‘click’ on object, query has spatial context Visualisation of results? For example,abstract 3D midi visualisaton with links

11 Semantic Web Technologies November

12 Semantic Web Technologies November Scenario 1 – this meeting! Our devices communicate using wireless/ad hoc networking, publishing information resources and associated metadata A hyperstructure (web) is created on-the-fly, enabling us to navigate our local information space. Links derived from metadata, metadata derived from documents; also bookmarks. When a message comes in (e.g. mobile phone call) it is routed appropriately to minimise invasiveness

13 Semantic Web Technologies November Scenario 2 – the musician Musician walks on stage with bluetooth guitar Musical devices on stage are located automatically, musician chooses to control appropriate instrument(s) Plays a few notes, musical score appears on private display More…the musician appears in virtual world, other musicians there too, playing virtual instruments, audible in physical world (AR meets VR)

14 Semantic Web Technologies November Scenario 3 – the information grid Group of experts deciding whether to make changes to production line in manufacturing organisation Use multiple simulations to investigate Processes farmed out across clusters (server farms) on WAN Visualise results locally, collaboratively Compare with results from previous runs (Is this The Web?)

15 Agents State of Play

16 Semantic Web Technologies November Software agents A buzzword for over 5 years now! Classic early papers:  ‘Agents that reduce work and information overload’ 1994  ‘Intelligent Agents: Theory and Practice’ 1995 The paradigm of weak agency is widely accepted, especially in the Web area There is a convenient subcategorisation into:  Personal and information agents  Multiagent systems

17 Semantic Web Technologies November Personal information assistants Personal assistants that collaborate with the user at the user interface Learning by ‘watching over their shoulders’, building and maintaining model of user Believable agents (cf traditional media) Movie/CD/book/document recommender agents exist, though with fairly weak user models For ‘people’, read ‘businesses’

18 Semantic Web Technologies November Multiagent systems Whole is greater than sum of the parts Requires agent communication languages (eg KQML, FIPA ACL) Ontology required – to agree the terms to be exchanged in communications Agent frameworks have emerged Few large scale systems exist

19 Semantic Web Technologies November Nwana’s appraisal “The ontology issues has always been considered secondary to other issues such as cooperation, negotiation, formalisation and logics for beliefs, desires and intentions, etc.... This problem is at the core of the agent interoperability issue – is it reasonable to expect knowledge and cooperation level interoperability without a significant degree of ontological sophistication of the agents concerned?” Nwana and Ndumu, A Perspective on Software Agents Research, BT Labs

20 Semantic Web Technologies November My appraisal XML, RDF(S) are useful infrastructure Need also to address…  Scalability – putting the ‘multi’ into multiagent!  Security – not just an add-on  Performance  Real systems!

21 Semantic Web Technologies November Current work Collaboration and negotiation between agents Market-based models, e.g. auctions See Applications in e-commerce but also telecoms Agents in the PIF; e.g. briefing room scenario – routing information in right format to right device at right time, taking account of security and invasiveness issues

22 Agents and metadata

23 Semantic Web Technologies November Agents… Use metadata to find resources and work with them They also create and maintain metadata For example, our ‘query by humming’ system  MIDI data gathered from net  Tidied  Channels classified and indexed  Queries routed by index servers  Results presented (e.g. SMIL) There is also metadata associated with the agents!

24 Semantic Web Technologies November Agents…recommender systems MEMOIR, an early agent-based recommender system Logged trails in object-oriented database Users could ask ‘who else has looked at these documents?’ and ‘what else did they look at?’ Later used keywords from docs in trails (and bookmarks) to model users Can now search and present results with a notion of context Through COHSE, will be able to navigate concept space

25 Semantic Web Technologies November

26 Semantic Web Technologies November Open Hypermedia Link database documents Note the direction of this arrow! Separable hyperstructure

27 Semantic Web Technologies November Hyperstructure as metadata Open hypermedia introduces separable hyperstructure, e.g. as supported through XLink Southampton model introduces reuseable separable hyperstructure, which can be applied to new documents Agents used for link resolution Agents build link databases and maintain them

28 Semantic Web Technologies November A case for streaming metadata? Three kinds of multimedia streams:  Media on demand  Live, one way  Two way Live metadata may be created by:  Producer (e.g Big Brother)  Video segmentation and classification  Annotation There are multiple simultaneous flows of data, from multiple sources Metadata needs to come from upstream in production process!

29 Onward to ontologies

30 Semantic Web Technologies November Agents using the Semantic Web Scenarios revisited:  Workshop scenario. Use ontology for our domain of interest. (And for IST?) Multimedia ontology for delivery of multimedia content.  Musician. Use ontology for navigating the musical information space. What about information about musical devices? Creation of metadata for new compositions.  Information grid. Ontologies for manufacturing and organisation. What about computational resources? Also need to find agents, and to communicate with them Hence working with multiple, distributed, ontologies.

31 Semantic Web Technologies November SoFAR SoFAR (the Southampton Framework for Agent Research) is a versatile multi-agent framework designed for Distributed Information Management tasks. SoFAR embraces the notion of proactivity as the opportunistic reuse of the services provided by other agents, and provides the means to enable agents to locate suitable service providers. SoFAR combines some ideas from the distributed computing community with the performative-based communications used in many agent systems: communications in SoFAR are based on the startpoint/endpoint paradigm, which is the foundation of Nexus, the communication layer at the heart of the Computational Grid.

32 Semantic Web Technologies November Index of /distrib/sofar024/ontology NameName Last modified Size DescriptionLast modifiedSizeDescription Parent DirectoryParent Directory 16-Nov :45 - actions/actions/ 16-Nov :45 - base/base/ 16-Nov :45 - fohm/fohm/ 16-Nov :45 - infrastructure/infrastructure/ 16-Nov :46 - metadata/metadata/ 16-Nov :45 - multimedia/multimedia/ 16-Nov :46 - system/system/ 16-Nov :45 - web/web/ 16-Nov :45 – Apache/1.3.9 Server at Port 80

33 Semantic Web Technologies November HyStream example Agents deal with multimedia streams ACL handles session control, synchronisation, linking Publish-subscribe Example predicates: u ContainsContour(music, contour, time) u Relay(multicast_address1, multicast_address2) The mediadata-metadata distinction becomes blurred, e.g. when features extracted from multimedia documents

34 Semantic Web Technologies November Agents supporting the Semantic Web Metadata, vocabularies, thesauri, ontologies are ‘stuff’ in the information space Note distinction between:  Automation of tasks, i.e. computer-to-computer interaction (a goal of XML et al)  Ontology capture and design tools involving humans Agents help with both; it’s the first that really helps agents (and is supported by current web technologies)

35 Semantic Web Technologies November The (distributed) intelligence Currently agents ‘wrap’ existing inference engines Agent Based Computing is an appropriate paradigm to work in complex world with multiple ontologies, fragments, multiple inferencing engines We anticipate further decomposition into multiple inferencing components

36 Semantic Web Technologies November Future work at Southampton Ontology support for agent collaboration and negotiation Ontologies and hypermedia (COHSE, Pervasive) Use of OIL/DAML Instantiating application-neutral ontologies for agent infrastructure Agents supporting the knowledge lifecycle

37 Summary

38 Semantic Web Technologies November Summary The fabric of the Web is changing DIM agents eat metadata for breakfast XML and RDF(S) support agent-agent interaction Agents not only use but also automate the construction and maintenance of metadata and ontologies

39 Semantic Web Technologies November Motivation “Consider a future device for individual use, which is a sort of mechanized private file and library. It needs a name, and to coin one at random, “memex” will do. 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. It is an enlarged intimate supplement to his memory” – Bush, July 1945 “There will always be plenty of things to compute in the detailed affairs of millions of people doing complicated things”


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