Abstract
Selfish agents in a multiagent system often behave suboptimal because they only intend to maximize their own profit. Therefore a dilemma occurs between the local optimum and the global optimum (i.e. optimizing the social welfare). We deal with a decision process based on multiple criteria to determine with whom to cooperate. We propose an imitation-based algorithm working locally on the agents and producing high levels of global cooperation. Without global knowledge the social welfare is maximized with the help of local decisions. These decisions are influenced by different meme values which are transmitted through the population.
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Eberling, M. (2009). Towards Determining Cooperation Based on Multiple Criteria. In: Mertsching, B., Hund, M., Aziz, Z. (eds) KI 2009: Advances in Artificial Intelligence. KI 2009. Lecture Notes in Computer Science(), vol 5803. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04617-9_69
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DOI: https://doi.org/10.1007/978-3-642-04617-9_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04616-2
Online ISBN: 978-3-642-04617-9
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