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Although computational models of cognition have become very popular, these models are relatively limited in their coverage of cognition-- they usually only emphasize problem solving and reasoning, or treat perception and motivation as isolated modules. The first architecture to cover cognition more broadly is Psi theory, developed by Dietrich Dorner. By integrating motivation and emotion with perception and reasoning, and including grounded neuro-symbolic representations, Psi contributes significantly to an integrated understanding of the mind. It provides a conceptual framework that highlights the relationships between perception and memory, language and mental representation, reasoning and motivation, emotion and cognition, autonomy and social behavior. It is, however, unfortunate that Psi's origin in psychology, its methodology, and its lack of documentation have limited its impact. The proposed book adapts Psi theory to cognitive science and artificial intelligence, by elucidating both its theoretical and technical frameworks, and clarifying its contribution to how we have come to understand cognition.
1: Machines to explain the mind
2: Dorner's "blueprint for a mind"
3: Representation of and for mental processes
4: Behavior control and action selection
5: Language and future avenues
6: Dorner's PSI agent implementation
7: From PSI to MicroPSI: Reprsentations in the PSI Model
8: The MicroPSI architecture
9: The MicroPSI framework
10: Summary: The PSI theory as a model of cognition
References
Index
