We show that adaptive agents on the Internet can learn to exploit bidding agents who use a (limited) number of fixed strategies. These learning agents can be generated by adapting a special kind of finite automata with evolutionary algorithms (EAs). Our approach is especially powerful if the adaptive agent participates in frequently occurring micro-transactions, where there is sufficient opportunity for the agent to learn online from past negotiations. More in general, results presented in this paper provide a solid basis for the further development of adaptive agents for Internet applications.

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Software Engineering [SEN]
Intelligent and autonomous systems

van Bragt, D.D.B, & La Poutré, J.A. (2002). Why agents for automated negotiations should be adaptive. Software Engineering [SEN]. CWI.