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).
Although the ultimate goal for Soar is to achieve general intelligence, there is no claim that this goal has already been reached. Advocates of the system recognize that Soar is still missing some important aspects of intelligence. Some examples of missing capabilities include automatically creating new representations on its own, such as through hierarchical clustering.
Read more about this topic: Soar (cognitive Architecture)
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