Decision Making Methods in Agent Based Modeling
نویسنده
چکیده
The aim of the work is to investigate how agents can become more intelligent using contemporary methods for decision making in electronic commerce auctions. The idea is to implement fuzzy logic for agents’ evaluations of market conditions and sort their preferences using difference combinations of fuzzy input data to make rational choice which is the best behavior under given market conditions. The task is to prove that a family of decision making algorithms, created in the Bulgarian Academy of Sciences, can be embedded in existing prototype of multi-agent simulator for online auctions for change of agents’ bidding strategy.
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