Intelligent animals are solutions to a design problem posed by: the varying requirements of individuals, the more permanent requirements of species and social groups, the constraints of the environment, and the available biological mechanisms. Analysis of this design problem, especially the implications of limited knowledge and a continuous flow of information in a rapidly changing environment, leads to a theory of how new motives are processed in an intelligent system. The need for speed leads to architectures and algorithms that are fallible in ways that explain why intelligent agents are susceptible to emotions and errors. This holds also for intelligent robots. A study of such mechanisms and processes is a step towards a computational theory of emotions, attitudes, moods, character traits, and other aspects of mind so far not studied in Artificial Intelligence. In particular, it turns out that no special emotional subsystem is required. This framework clarifies and refines ordinary concepts of mental processes, and suggests a computational approach to psychotherapy.
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