Evaluating Reputation in Multi-agents Systems

Reputation has recently received considerable attention within a number of disciplines such as distributed artificial intelligence, economics, evolutionary biology, among others. Most papers about reputation provide an intuitive approach to reputation which appeals to common experiences without clarifying whether their use of reputation is similar or different from those used by others. This paper argues that reputation is not a single notion but one with multiple parts. After a survey of existing works on reputation, an intuitive typology is proposed summarizing existing works on reputation across diverse disciplines. This paper then describes a simple simulation framework based on evolutionary game theory for understanding the relative strength of the different notions of reputation. Whereas these notions of reputation could only be compared qualitatively before, our simulation framework has enabled us to compare them quantitatively.

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