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Soar (cognitive architecture)
Soar〔 is a cognitive architecture,〔 created by John Laird, Allen Newell, and (Paul Rosenbloom ) at Carnegie Mellon University , now maintained by John Laird's research group at the University of Michigan. It is both a view of what cognition is and an implementation of that view through a computer programming architecture for artificial intelligence (AI). Since its beginnings in 1983 and its presentation in a paper in 1987,〔Laird, Rosenbloom, and Newell (1987). "Soar: An Architecture for General Intelligence". ''Artificial Intelligence'', 33: 1-64〕 it has been widely used by AI researchers to model different aspects of human behavior.
== Theory ==
The main goal of the Soar project is to be able to handle the full range of capabilities of an intelligent agent, from highly routine to extremely difficult open-ended problems. In order for that to happen, according to the view underlying Soar, it needs to be able to create representations and use appropriate forms of knowledge (such as procedural, declarative, episodic). Soar should then address a collection of mechanisms of the mind. Also underlying the Soar architecture is the view that a symbolic system is essential for general intelligence (see brief comment on ''neats'' versus ''scruffies''). This is known as the ''physical symbol system hypothesis''. The views of cognition underlying Soar are tied to the psychological theory expressed in Allen Newell's book, ''Unified Theories of Cognition''.〔
While symbol processing remains the core mechanism in the architecture, recent versions of the theory incorporate non-symbolic representations and processes, including reinforcement learning, imagery processing, and emotion modeling (Laird, 2008). Soar's capabilities have always included a mechanism for creating new representations, by a process known as "chunking". Ultimately, Soar's goal is to achieve general intelligence, though this is acknowledged to be an ambitious and possibly very long-term goal.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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