We propose a new framework for reasoning about the reputation of multiple agents, based on the partially observable Markov decision process (POMDP). It is general enough for the specification of a variety of stochastic multi-agent system (MAS) domains involving the impact of agents on each other’s reputations. Assuming that an agent must maintain a good enough reputation to survive in the system, a method for an agent to select optimal actions is developed.
CITATION STYLE
Rens, G., Nayak, A., & Meyer, T. (2018). Maximizing expected impact in an agent reputation network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11117 LNAI, pp. 99–106). Springer Verlag. https://doi.org/10.1007/978-3-030-00111-7_9
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