1. TAGA An Advanced Trading Agent Framework
Youyong Zou, Li Ding,
Harry Chen, Rong Pan, Tim Finin
University of Maryland, Baltimore County
April 2003

2. Overview
The Trading Agent Competition has advanced the theory and practice of agent-based dynamic markets
TAC has an abstract and overly simplified model of multiagent systems.
TAGA is an enhanced environment for experimenting with agent-based dynamic markets using important new technologies:
FIPA standards for agent communication
OWL for ontologies and content
DAML-S for describing and reasoning about services
Taga is intended as a research and teaching testbed for both dynamic markets and agents and the semantic web
Taga was recognized as the best student entry in the 2003 EU agent technology competition.

3. Outline Review of TAC The need for a more realistic model
The TAGA model
Semantic web in TAGA
Future directions
Conclusions

4. Review of TAC

5. TAC
The Trading Agent Competition proposed (1999) and first run (2000) by Mike Wellman and Peter Wurman
International competitions in 2000, 2001 and 2002 were based on a simple travel scenario
2003 will have two competitions:
TAC classic – travel agency scenario
TAC SCM – supply chain management scenario
The finals will be held at IJCAI in August
See

6. TAC Classic
In a game instance, 8 travel agencies compete to satisfy their clients, buying flights, hotel rooms and entertainment tickets in various markets.

7. TAC Classic Trading Agents TAC Server Market server Game Spectators
Communication
with trading
agents
Market
server
Information
database
Publish data
via web and
applet
TAC Server
Trading Agents
Game Spectators
Living
Agents
ATTac
006
TAC Classic

8. Market Game Rules: Packages
Inbound flight Days 1-4
Outbound flight Days 2-5
Hotel reservation Days 1-4, Good or Cheap
Entertainment tickets Days 1-4, AP, AW, or MU
*2 + 4*3 = 28 auctions

9. Client Utilities Utility=1000-travelPenalty+hotelBonus+funBonus
IAD: Ideal Arrival Date IAD=1..4
IDD: Ideal Departure Date IDD=2..5
HV: Value for Good Hotel HV=
AP: Amusement Park AP=0..200
AW: Alligator Wrestling AW=0..200
MU: Museum MU=0..200
Utility=1000-travelPenalty+hotelBonus+funBonus
Travel Penalty = 100*(|IAD-AD|+|IDD-DD|)
hotelBonus = HV, if Good hotel
funBonus = AP + AW + MU, if package includes resp. entertainment

10. Auctions: Flights Unlimited supply, continuous clearing
Initial price within $[250;400], max = $800
Every sec, price perturbed by a random value drawn from [-10; x(t)]
Perturbations biased upwards:
x(t) = 10+(C – 10)*(t / 720),
C is a number, drawn uniformly from [10;90]

11. Auctions: Hotels Seller makes available 16 rooms per night
Rooms sold in ascending, multi-unit, 16th price auctions:
Top 16 bids win
winners pay 16th highest price
Hotel auctions close randomly every minute to avoid late bidding

12. Auctions: Entertainment
Continuous double auctions
Each agent receives random initial endowment of tickets

14. The need for a more realistic model

15. Real World Issues
TAC classic assumes that agents interact via a few centralized markets.
Technology is basically client-server with well defined APIs and simple XML encodings.
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
Bilateral negotiation for information and services is common
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.

16. Our Research Objective
To develop an agent framework for building simulations of the traveling business
Using the Agentcities to support the Trading Agent Competition in a global scale
Using the Semantic Web languages & tools to enable ontology sharing and reasoning
Extending the FIPA protocols to support open market auctions and agent negotiations

17. TAGA

18. Travel Agent Game in Agentcities
Game Objective: develop strategies for different agents to achieve their objectives
You can choose to implement:
Customer Agent
Web Service
Agent
Travel Agent OR OR

19. The UMBC TAGA Demo What we have developed and achieved
Travel Agent Game in Agentcities (TAGA)
A FIPA compliant agent framework that extends and enhances the Trading Agent Competition (TAC)
Project won the Best Student Entry in the Agentcities sponsored Agent Technology Competition held in Feb in Barcelona
Our main contributions
Auction services are developed to enrich the Agentcities environment
The use of Semantic Web languages (OWL) improves agent interoperability
DAML-S ontology is employed to support service registration, discovery and invocation.
The development of TAGA is an attempt to bring Trading Agent Competition (TAC) into a more realistic e-commerce world. In TAGA, agents can use auctions and other markets but can also interact directly with one another, buying, selling, querying, etc.
Our objectives include:
(1) Developing an open framework for building trading game simulation;
(2) Developing a MAS research testbed for studying complex intelligent agent behavior; and
(3) Developing a MAS teaching tool that helps beginners to have a hands-on experience in building software agents.

20. The TAGA Game and Players
Game Objective: develop strategies for different agents to achieve their objectives
Human players can choose to implement/play agents with different objectives:
Customer Agent
(CA)
find travel arrangements
try to save $$
Travel Agent
(TA)
satisfy customers’ needs
maintain a good reputation
try to maximize profits
Web Service
Agent
(WSA)
sell “goods” (e.g., plane tickets, hotel rooms, entertainment tickets)
TAGA provides default agent shells
Anyone can download a copy of the default agent, customize it and participate in the game.
Users can also develop customized agent strategies to compete with other agents.
Agents must follow well defined, industry supported standards for agent communication languages and protocols
Based on TAGA, researchers can develop more advanced agent models involving distributed trust, social norms, reputation models, security and/or privacy considerations.

21. TAGA in Action Our Demo Will Show …
TAGE Home Page
Create a TAGA game online
Download the latest TAGA pkg and docs
TAGA on Agentcities network
(UMBCTac.agentcities.net)
Baltimore, MD USA
Our Demo Will Show …
The architectural design of TAGA including ontologies, agent communication languages, negotiation protocols and agent development shells.
The runtime features of a TAGA game server -- a multi-tier web application involving web severs, remote Java applications, FIPA platforms, and the semantic web.
The runtime interactions of different TAGA agents including the complete run of a typical TAGA scenario.
How to customize and extend the TAGA framework for research and teaching purposes
TAGA supports heterogeneous agent platform.
A FIPA-JADE agent can interact with a FIPA-AAP agent

22. A Typical Scenario Hotel WS Airline WS Market Oversight Agent Bulletin4
Airline WS 6
Market Oversight Agent 3
Bulletin
Board
Auction
Service
(1) Every 30 sec., a customer agent (CA) with random travel profiles posts a request on the Bulletin Board.
(2a) The Bulletin Board forwards the request to all registered TA (calling for travel package proposal)
(2b) CA considers incoming proposals submitted by different TA using its own utility function & chooses 1 winning TA.
(3) The chosen TA attempts to put together a travel package for the CA using its built-in strategies (e.g., buying plane tickets through auction & reserving hotel rooms directly from the online web services)
(4) After each successful transaction, $$ are deposited to the accounts of the WS in the Market Oversight Agent
(5) Once TA has made a complete travel package, it informs its client CA.
(6) Upon receiving the travel package, CA deposits $$ into the TA’s account in the Market Oversight Agent. CA TA 1 2a 2b 5

23. The TAGA Game Server http://taga.umbc.edu/taga/play/demo.htm
View TAGA game status
View ACL message traffic
Monitor Open Market Auction
TAGA is constantly running as part of the Agentcities network ( which connects 134 registered agent platforms and agent services
The TAGA implementation is robust and flexible. TAGA agents can dynamically join and leave the system without interrupting the execution of other agents in the system.
TAGA has a robust Apache + MySQL web back-end system and a highly customizable PHP web scripting front-end.
Agents that are implemented in either JADE and AAP can interact with the server.
Monitor Customer Agents
(and more … new agent, user login, create game, game history)

24. TAGA Now and in the Future
Add more reasoning to TAGA agents
Use OWL-S for service discovery and planning
Add more demonstration agents
Develop toolkit for teaching agent and SW technology
Open Source
Now
Built on FIPA standards: Agentcities + April Agent Platform (AAP) + JADE
Employs OWL ontologies in agent communication
Uses SOAP & WSDL in Web Service registrations
Robust & persistent web server backend (MySQL + PHP + Apache)
We have successfully demonstrated TAGA and won a prize in the Agent Technology Competition in Feb. 2003, which was held in conjunction with the third Information Day organized by the Agentcities.NET project.
For more information see for
Mailing lists
News & documentation
Contact info
and more …
For more info:

25. Prototype Implementation
Travel Agent Contracts
Static contract: the system assigns each TA with a fixed number of CA (in TAC-02)
Dynamic contract: Each TA bids for its own clients through the Bulletin Board Agent
Auction Service Agent
English & Dutch auction
“Name your price” auction (priceline.com & hotwire.com)

26. TAGA and the Semantic web

27. TAGA and the semantic web
Semantic web languages and tools are used in several ways in TAGA
To specify and publish the underlying common ontologies
As a content language within the FIPA ACL messages
As the basis for agent KBs via an XSB-based reasoning tools
To describe and reason about services

28. TAGA Ontologies Travel.owl – travel related concepts
Auction.owl – models for different kinds of auctions and markets
Fiapowl.owl – Owl as a FIPA compliant content language
Tagaql.owl – a simple query language

29. Examples…

30. Future work and conclusions

31. Future Work Package TAGA for Open Source
AAP/JADE agent shells for various kinds of agents: CA, TA & WSA
TAGA protocols for registration, logging etc.
Use OWL-S for service description and matching
Provide new classes of agents, e.g. a reputation server
Exploit ontology reasoning

32. TAGA Significant Features
An extensible and open framework for the Trading Agent Competition (TAC)
TAGA explores the use of Semantic Web languages (OWL) in a multi-agent environment.
Persistent gaming service
Players can dynamically join & leave the game
UMBC TAGA platform has been running on the Agentcities network for more than 100 days

33. For more information