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

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

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

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

May 6, 2004 5

OWL as ACL Content Language

I. OWL’s 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

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 FIPA’s standard content languages OWL is widely used for publishing ontologies

within the FIPA community, for example, agentcities and openNet

May 6, 2004 7

FIPA Standards Overview

EnvelopeEncodingScheme

ACLEncodingScheme

CLEncodingScheme

TransportProtocol

InteractionProtocol

Envelope1 11 isTransmittedOver

Ontology

Message1

ACL

1

isExpressedIn1..*

1

1..*

1

contains

ContentLanguage

Symbol11..* 11..*

belongsTo

Content

1

1

1

1

contains

11 11

isExpressedIn

0..*

1

0..*

1

contains

1

IIOPHTTP

ACL

SL

fipa-agent-management

IDLXMLbit-eff

StringXMLbit-eff

String

request, query, request-whencontract-net, iterated-contract-netbrokering, recruitingsubscribe, propose

Owl as a content languag

e

Owl for ontologies

Owl for publishin

g protocols

Owl for publishing

communicative acts

--Tim Finin 2003

May 6, 2004 8

FIPA Agent Platform

AMS DF ACC

internal platform message transport

AAsoftware

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

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

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

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

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.

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

May 6, 2004 14

A Typical ScenarioA Typical Scenario

BulletinBoard

CA TA

AuctionService

Airline WSHotel WS

1 2a

3

4

5

6

2b

Market Oversight Agent

May 6, 2004 15

TAGA Agents (1)……..

Customer Agents

One CA joins the Game every 30 Sec.

Hotel Web Service

EntertainmentWeb 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

May 6, 2004 16

TAGA Agents (2)

Market OversightAgent

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

May 6, 2004 17

Dynamic Contract Protocol

May 6, 2004 18

Priceline Auction Protocol

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

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 (priceline.com &

hotwire.com)

Travel Agent Game in Agentcities

http://taga.umbc.edu/

TechnologiesTechnologiesFIPA (JADE, April Agent Platform)

Semantic Web (RDF, OWL)

Web (SOAP,WSDL,DAML-S)

Internet (Java Web Start )

FeaturesFeaturesOpen Market FrameworkAuction ServicesOWL message contentOWL OntologiesGlobal Agent Community

MotivationMotivationMarket dynamicsAuction theory (TAC)Semantic webAgent collaboration (FIPA & Agentcities)

Travel Agents

Auction Service Agent

Customer Agent

Bulletin BoardAgent

Market Oversight Agent

Request

Direct Buy

Report Direct Buy Transactions

BidBid

CFP

Report Auction Transactions

Report Travel Package

Report Contract

Proposal

Web Service Agents

OntologiesOntologieshttp://taga.umbc.edu/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 negotiatio

n

Owl as a content languag

e

Owl for publishing

communicative acts

Owl for contract

enforcement

Owl for modeling trust

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

May 6, 2004 23

Ontologies ACL

http://taga.umbc.edu/ontologies/fipaowl.owl Auction

http://taga.umbc.edu/ontologies/auction.owl Travel

http://taga.umbc.edu/ontologies/travel.owl

Submitted to DAML ontology library

May 6, 2004 24

Multiple Ontologies Support NewInstance OntologyQuery OntologyShare OntologyRelation

Agent A

Agent B

NewInstance

Agent A

Agent B

Agent B

Agent A

OntologyShare

OntologyQuery

OntologyQuery

OntologyRelation

May 6, 2004 25

TAGA in ActionTAGA in ActionTAGE Home Pagehttp://taga.umbc.edu

TAGA on Agentcities network(UMBCTac.agentcities.net)Baltimore, MD USAhttp://www.agentcities.net/

Download the latest TAGA pkg and docshttp://taga.umbc.edu/taga/download/

Create a TAGA game online

TAGA supports heterogeneous agent platform.A FIPA-JADE agent can interact with a FIPA-AAP agent

May 6, 2004 26

Conclusion (1)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

May 6, 2004 27

Conclusion (2)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.