Combining theory of mind and abductive reasoning in agent-oriented programming

This paper presents a novel model, called T om A bd , that endows autonomous agents with Theory of Mind capabilities. T om A bd agents are able to simulate the perspective of the world that their peers have and reason from their perspective. Furthermore, T om A bd agents can reason from the perspective of others down to an arbitrary level of recursion , using Theory of Mind of n^th order. By combining the previous capability with abductive reasoning, T om A bd agents can infer the beliefs that others were relying upon to select their actions, hence putting them in a more informed position when it comes to their own decision-making. We have tested the T om A bd model in the challenging domain of Hanabi, a game characterised by cooperation and imperfect information. Our results show that the abilities granted by the T om A bd model boost the performance of the team along a variety of metrics, including final score, efficiency of communication, and uncertainty reduction.