A biological decision-theoretic intelligent agent solution to a herding problem in the context of distributed multi-agent systems

Abstract

Proposes a biological decision-theoretic intelligent agent model to solve a herding problem. The proposed intelligent agent model is designed by combining Bayesian networks and influence diagrams. In our agent design, we used Y. Shoham's (1993) agent-oriented programming paradigm that defines an intelligent agent by its belief, preference and capabilities. Intelligent agent software is written to realize the proposed intelligent agent model. The same software is then used to simulate the herding problem with one sheep and one dog. Simulation results show that the proposed intelligent agent is successful in establishing a goal (herding) and learning other agents' behaviors.