This paper presents an architecture for a memory model that facilitates versatile reasoning mechanisms over the beliefs stored in an agent’s belief base. Based on an approach for belief aggregation, a model is introduced for controlling both the formation of and complex beliefs and the retrieval of them based on their activation history. An implementation of the presented mechanisms illustrates how it can be used in intelligent agents that exhibit human-like (biased) reasoning as well as rational reasoning.
Annerieke Heuvelink, Michel C. A. Klein, Jan Treur