Evolution of intelligent agent in auction market

This work presents a fuzzy mental model to address evolution of intelligent agents in virtual market. Agent fitness and fuzzy multi-criteria decision-making are proposed as evolution mechanisms, and fuzzy soft goals are introduced to facilitate the evolution process. Genetic programming operators are employed to restructure agents in the proposed multi-agent evolution cycle. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve based on the context and the bidding stance of the agent's opponent.