Abstract
A Boolean game models situations in which each agent of a game holds a distinct set of Boolean variables, and has a goal it attempts to satisfy. However, at system level, there may be either constraints or a global goal to be fulfilled. Therefore, it is necessary to design a mechanism that provides incentives to the agents to align their individual goals with the global goal. It has been proven that designing such a mechanism is hard. Therefore, in this paper we propose the use of an evolutionary approach to mechanism design so that the system reward is optimized. This has a potential impact in distributed as well as multiagent systems, where agents often face binary decisions. Examples are minority and congestion games in general, as, e.g., the El Farol Bar Problem. Our results show that using a genetic algorithm one can evolve a configuration in which agents have Boolean functions that make them act in a way that is aligned with a global goal.
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Galafassi, C., Bazzan, A.L.C. (2013). Evolving Mechanisms in Boolean Games. In: Klusch, M., Thimm, M., Paprzycki, M. (eds) Multiagent System Technologies. MATES 2013. Lecture Notes in Computer Science(), vol 8076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40776-5_9
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DOI: https://doi.org/10.1007/978-3-642-40776-5_9
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