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The definitive presentation of Soar, one AI's most enduring
architectures, offering comprehensive descriptions of fundamental
aspects and new components. In development for thirty years, Soar
is a general cognitive architecture that integrates
knowledge-intensive reasoning, reactive execution, hierarchical
reasoning, planning, and learning from experience, with the goal of
creating a general computational system that has the same cognitive
abilities as humans. In contrast, most AI systems are designed to
solve only one type of problem, such as playing chess, searching
the Internet, or scheduling aircraft departures. Soar is both a
software system for agent development and a theory of what
computational structures are necessary to support human-level
agents. Over the years, both software system and theory have
evolved. This book offers the definitive presentation of Soar from
theoretical and practical perspectives, providing comprehensive
descriptions of fundamental aspects and new components. The current
version of Soar features major extensions, adding reinforcement
learning, semantic memory, episodic memory, mental imagery, and an
appraisal-based model of emotion. This book describes details of
Soar's component memories and processes and offers demonstrations
of individual components, components working in combination, and
real-world applications. Beyond these functional considerations,
the book also proposes requirements for general cognitive
architectures and explicitly evaluates how well Soar meets those
requirements.
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