Behaviors that emerge from emotion and cognition: implementation and evaluation of a symbolic-connectionist architecture

This paper describes the implementation and evaluation of a framework for modeling emotions in complex, decision-making agents. Sponsored by U.S. Army Research Institute (ARI), the objective of this research is to make the decision-making process of complex agents less predictable and more realistic, by incorporating emotional factors that affect humans. In tune with modern theories of emotions, we regard emotions essentially as subconscious signals and evaluations that inform, modify, and receive feedback from a variety of sources including higher cognitive processes and the sensorimotor system. Thus, our work explicitly distinguishes the subconscious processes (in a connectionist implementation) and the decision making that is subject to emotional influences (in a symbolic cognitive architecture).It is our position that "emotional states" are emergent patterns of interaction between decision-making knowledge and these emotional signal systems. To this end, we have adopted an approach that promotes the emergence of behavior as a result of complex interactions between factors affecting emotions, integrated in the connectionist-style model, and factors affecting decision making, represented in the symbolic model.This paper presents the implementation of emotions architecture and explains how we evaluated the system. This includes a description of the behaviors we used in our prototype, the design of our experiments, a representative set of behavior patterns that emerged as a result of exercising our model over the design space, and our project's lessons learned.