Connectionist Models for Learning Choice Behaviour in Reactive Software

This paper proposes a model of reactive action selection specialised for intelligent software agents. It explores the role of connectionism in providing a computational model of adaptive action selection. Then, the general properties of a network necessary to implement reactive action selection are considered and an architecture proposed. Throughout, similarities with other action selection and connectionist architectures are highlighted. The paper concludes by exploring an application.