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AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Reasoning about Uncertainty
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
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Acquiring domain knowledge for negotiating agents: a case of study
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Economic mechanism design for computerized agents
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An e-market framework for informed trading
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Automated trading: making it happen
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Towards Information and Goal Based Agent Negotiation
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Building an electronic market system
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An approach to auctions and bidding is founded on observations and expectations of the opponents' behavior and not on assumptions concerning the opponents' motivations or internal reasoning. A bidding agent operates in an information-rich environment that includes real-time market data and data extracted from the World Wide Web. This agent employs maximum entropy inference to determine its actions on the basis of this uncertain data. Maximum entropy inference may be applied both to multi-issue and to single-issue negotiation. Multi-issue variants of the four common auction mechanisms are discussed.