Reinforcement Learning and Animat Emotions

Emotional states, such as happiness or sadness, pose particular problems for information processing theories of mind. Hedonic components of states, unlike cognitive components, lack representational content. Research within Artiicial Life, in particular the investigation of adaptive agent architectures, provides insights into the dynamic relationship between motivation, the ability of control sub-states to gain access to limited processing resources, and prototype emotional states. Holland's learning classiier system provides a concrete example of this relationship, demonstrating sim-plèemotion-like' states, much as a thermostat demonstrates simplèbelief-like' and`desire-like' states. This leads to the conclusion that valency, a particular form of pleasure or displeasure , is a self-monitored process of credit-assignment. The importance of the movement of a domain-independent representation of utility within adaptive archi-tectures is stressed. Existing information processing theories of emotion can be enriched by a `circulation of value' design hypothesis. Implications for the development of emotional animats are considered.