BDI Agents with Fuzzy Perception for Simulating Decision Making in Environments with Imperfect Information

This work introduces a model of fuzzy perception for BDI agents, to support the simulation of decision making processes in environments with imperfect information. An application to a fuzzy prey-predator environment was developed, as an example, where the process of deciding which prey a predator should attack is based on its fuzzy perception of the strength of the prey, and on the comparison of the preys’ strengths with its own strength. Different simulations were realized for the comparative evaluation of different types of predator agents, in contexts with and without competition between predators. The quantitative analysis of the simulations shows that the fuzzy predator agent presents the best scores. However, the important result is that the fuzzy predator seems to behave more adequately in the environment, in the sense that it presents an apparently more natural, coherent and realistic behavior.