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This paper presents an application of Interval- valued Hidden Markov Models to the modelling of agent personality traits in multiagent systems. The agents' behaviors are modeled as probabilistic tran- sitions functions, where interval-valued probabili- ties are used to express the uncertainty in determin- ing those probabilities. The model of regulation of social exchanges is based on the concept of super- visor of equilibrium, which is able to recommend the best exchanges that the agents may perform in order to achieve the equilibrium of the system.

Interval-Valued Hidden Markov Models for Recognizing Personality Traits in Social Exchanges in Open Multiagent Systems