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May 6, 2004 1 Service agents Publish white page services description content and register the services at a yellow page site Understand ontology and answer.

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Presentation on theme: "May 6, 2004 1 Service agents Publish white page services description content and register the services at a yellow page site Understand ontology and answer."— Presentation transcript:

1 May 6, 2004 1 Service agents Publish white page services description content and register the services at a yellow page site Understand ontology and answer queries Link with the semantic web server and push information to other agents

2 May 6, 2004 2 Features Distributed: no centralized agent who has to search all web pages and understand every ontology The best agent to ask questions can be easily located: a good amendment to the web services discovery and the agent services searching The non-semantic web site joins the semantic world by linking to a service agent The non-agent program can be wrapped with a service agent shell Trustworthy: Owned by the semantic web site

3 May 6, 2004 3 Function Level I. Provide the requested semantic web page II. Answers simple questions about the semantic web pages: The inference in this level is based on local rules, limited semantic pages and local ontologies III. Answer complicated questions about the semantic web pages: The inference in this level involves multiple ontologies, multiple semantic web sites and multiple agents IV. Validates trust and delegation

4 May 6, 2004 4 OWL as a Semantic Language Well-defined model-theoretic semantics Unambiguously computer-interpretable Facilitates a higher-level of interoperability between the agents By agreeing on how meaning is conveyed, applications can share meaningful content easily and naturally

5 May 6, 2004 5 OWL as ACL Content Language I.OWLs expressive power is adequate for many needs of current agent based systems II.OWL offers better support for using terms drawn from multiple namespaces and multiple ontologies than existing ACL content languages III.OWL provides improved support in modeling, maintaining and sharing ontologies IV.OWL is designed to fit into and integrate with web- based information and web services V.OWL has the potential to be a widely accepted and used representation language, enhancing the potential for interoperability among many systems

6 May 6, 2004 6 Semantic Web in FIPA FIPA is the most widely used MAS framework Well developed and documents standards Good open source software RDF is one of FIPAs standard content languages OWL is widely used for publishing ontologies within the FIPA community, for example, agentcities and openNet

7 May 6, 2004 7 FIPA Standards Overview EnvelopeEncodingScheme ACLEncodingScheme CLEncodingScheme Transport Protocol InteractionProtocol Envelope 1 1 1 isTransmittedOver Ontology Message 1 ACL 1 isExpressedIn 1..* 1 1 contains Content Language Symbol 11..*1 belongsTo Content 1 1 1 1 contains 1111 isExpressedIn 0..* 1 1 contains 1 IIOP HTTP ACL SL fipa-agent-management IDL XML bit-eff String XML bit-eff String request, query, request-when contract-net, iterated-contract-net brokering, recruiting subscribe, propose Owl as a content language Owl for ontologies Owl for publishing protocols Owl for publishing communicative acts --Tim Finin 2003

8 May 6, 2004 8 FIPA Agent Platform AMSDFACC internal platform message transport AA software IIOP Agents belong to one or more agent platforms which provide basic services. Owl for service descriptions Owl for authorization policies Owl for representation and reasoning Owl for user models and profiles --Tim Finin 2003

9 May 6, 2004 9 Outline Part 1: Thesis and Contribution Part 2: Background Part 3: Research Question Part 4: Agent-Based Services Part 5: TAGA and F-OWL Part 6: Conclusion

10 May 6, 2004 10 Why TAGA ? Need a big and complicated system to evaluate the ideas Agentcities provides a robust global agent services platform TAC is a successful travel market simulation system

11 May 6, 2004 11 Trading Agent Competition The Trading Agent Competition proposed (1999) and first run (2000) by Michael Wellman and Peter Wurman Goal: promote and encourage research in markets involving autonomous trading agents; Methods: trading agents operate within a travel market scenario; International competitions in 2000, 2001 and 2002 were based on a simple travel scenario

12 May 6, 2004 12 Problems TAC classic assumes that agents interact via a few centralized markets. Technology is basically client-server with well defined APIs and simple XML encoding. Real word interactions are varied and rich Customers can chose to interact with travel agencies, dynamic markets, or directly with service providers Choices are governed by value, speed, reputation Rich information exchange abounds -- customers have complex interests and preferences, service providers have detailed descriptions, etc. Common ontologies are important Trust and reputations are important.

13 May 6, 2004 13 TAGA Features Open Market Framework Auction Services OWL Message Content Travel Market Ontology Global Agent Community Goal: test bed for experimenting with Agents, Semantic Web and Web Services

14 May 6, 2004 14 A Typical Scenario Bulletin Board CA TA Auction Service Airline WS Hotel WS 12a2a 3 4 5 6 2b2b Market Oversight Agent

15 May 6, 2004 15 TAGA Agents (1) …. Customer Agents One CA joins the Game every 30 Sec. Hotel Web Service Entertainment Web Service Airline Web Service TA-1 (AAP)TA-2 (AAP)TA-4 (JADE) Find travel arrangements Save $$ Organize travel Maximize profits sell goods Maximize profits

16 May 6, 2004 16 TAGA Agents (2) Market Oversight Agent Auction Service Agent Helps CA find one or more TA Operates the auctions markets: English, Dutch, Priceline and Hotwire. Manage the financial records Announces the winning TA Bulletin Board Agent

17 May 6, 2004 17 Dynamic Contract Protocol

18 May 6, 2004 18 Priceline Auction Protocol

19 May 6, 2004 19 Technology System Infrastructure: Agentcities + AAP + JADE Travel and Auction Ontologies: OWL Web Services: WSDL Web technology: Apache, MySQL Java Web Start Agent Communication: FIPA (OWL as the content language) Service registration: OWL-S

20 May 6, 2004 20 Simulation Design Game running continuously Travel Agent Direct Buy or Bid Acquire resource before or after win customer Penalty, reputation Auction Service Agent English & Dutch auction Name your price auction ( &

21 Travel Agent Game in Agentcities Technologies FIPA (JADE, April Agent Platform) Semantic Web (RDF, OWL) Web (SOAP,WSDL,DAML-S) Internet (Java Web Start )Features Open Market Framework Auction Services OWL message content OWL Ontologies Global Agent CommunityMotivation Market dynamics Auction theory (TAC) Semantic web Agent collaboration (FIPA & Agentcities) Travel Agents Auction Service Agent Customer Agent Bulletin Board Agent Market Oversight Agent Request Direct Buy Report Direct Buy Transactions Bid CFP Report Auction Transactions Report Travel Package Report Contract Proposal Web Service Agents Ontologies Ontologies travel.owl – travel concepts fipaowl.owl – FIPA content lang. auction.owl – auction services tagaql.owl – query language FIPA platform infrastructure services, including directory facilitators enhanced to use OWL-S for service discovery Owl for representation and reasoning Owl for service descriptions Owl for negotiation Owl as a content language Owl for publishing communicative acts Owl for contract enforcement Owl for modeling trust

22 May 6, 2004 22 ACL Content Statements: the price of this hotel in day 3 is $100/night; Requests: create an airline auction instance; Contracts: if the Travel Agent TA1 successful organized the travel package, customer Joe will pay $400 to TA1, else, TA1 pay $200 compensation to Joe. Policies: to win the contract of the customer Joe, the travel agent must have reputation better than average

23 May 6, 2004 23 Ontologies ACL Auction Travel Submitted to DAML ontology library

24 May 6, 2004 24 Multiple Ontologies Support NewInstance OntologyQuery OntologyShare OntologyRelation Agent AAgent B NewInstance Agent A Agent B Agent A OntologyShare OntologyQuery OntologyRelation

25 May 6, 2004 25 TAGA in Action TAGE Home Page TAGA on Agentcities network ( Baltimore, MD USA Download the latest TAGA pkg and docs Create a TAGA game online TAGA supports heterogeneous agent platform. A FIPA-JADE agent can interact with a FIPA-AAP agent

26 May 6, 2004 26 Conclusion (1) A rich framework for exploring agent-based approaches to e-commerce applications. Auction services are developed to enrich the Agentcities environment The use of Semantic Web languages (OWL) improves agent interoperability OWL-S is employed to support agent service registration, discovery and invocation A sourceforge project

27 May 6, 2004 27 Conclusion (2) Won the Best Student Entry in the Agentcities sponsored Agent Technology Competition held at Barcelona in Feb. 2003 TAGA platforms have been running in Agentcity.Net for more than 16 months. Invited to Intelligent System Demonstrations at IJCAI 2003 and AAMAS 2004 Used by people from US, Korea, Romania, etc.

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