Abstract
This paper suggests an evolutionary approach to design coordination strategies for multiagent systems. Emphasis is given to auction protocols since they are of utmost importance in many real world applications such as power markets. Power markets are one of the most relevant instances of multiagent systems and finding a profitable bidding strategy is a key issue to preserve system functioning and improve social welfare. Bidding strategies are modeled as fuzzy rule-based systems due to their modeling power, transparency, and ability to naturally handle imprecision in input data, an essential ingredient to a multiagent system act efficiently in practice. Specific genetic operators are suggested in this paper. Evolution of bidding strategies uncovers unknown and unexpected agent behaviors and allows a richer analysis of auction mechanisms and their role as a coordination protocol. Simulation experiments with a typical power market using actual thermal plants data show that the evolutionary, genetic-based design approach evolves strategies that enhance agents profitability when compared with the marginal cost-based strategies commonly adopted
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
