Designing the Market Game for a Trading Agent Competition
IEEE Internet Computing
Making Rational Decisions Using Adaptive Utility Elicitation
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
An agenda-based framework for multi-issue negotiation
Artificial Intelligence
The 2003 Supply Chain Management Trading Agent Competition
ICEC '04 Proceedings of the 6th international conference on Electronic commerce
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In this game, agents will face-off against each other in the ultra-competitive real estate market. Each competitor will act as a real estate agent, working on behalf of clients who need to move into new homes. These clients need to buy a new home as well as sell their current home. The game will test competitors' technology in two main research areas: preference elicitation and multi-issue negotiation. Each time an agent acquires a new client, it must query the client about its various preferences (e.g. price range, number of bedrooms, etc.) for their new home. Agents then search the listings of the other agents, seeking a possible match. Once found, the agent then engages in negotiations with the selling agent, haggling over various aspects of the deal. Once a house has been purchased, the client's old house needs to be sold. The objective of the game is to earn the most money. Selling agents earn commissions from sales. Buying agents do not earn commissions, but instead need to maximize the utility of their clients by obtaining a good deal. Satisfied clients are more likely to keep their agent to sell their old house.