Unified Theories of Cognition

Unified Theories of Cognition

A unified theory is a theory which attempts to explain the details of all mechanisms of all problems within some domain. All previous results should be reproduced and explained. A unified theory of cognition has as its domain all of the cognitive behavior of humans. Newell (1990) proposed that the current state-of-the-art in experimental psychology could now support such theories, based on years of accumulated results. These results are often clustered into more or less independent areas of specialization. For example, the ability to process language is independent of the ability to memorize dates, to solve mathematical problems, and the ability to learn to ski moguls. Non-cognitive psychological behavior is not included.

To assert a unified theory of cognition, one must propose mechanisms by which the results of these human cognitive experiments can be reproduced. The codification and simulation of these mechanisms is tantamount to designing an architecture for general intelligence. In this sense, if one wishes to build an artificially intelligent agent using the human as model, the architecture proposed for the agent could be considered a unified theory of cognition.

The development of a unified theory of cognition has been driven by the need or desire for an empirical argument or analytical proof of the sufficiency of a symbol-level system to support general intelligence. Without analytical tools to determine the necessary or sufficient structure needed to support some capability, it becomes tempting to build an agent that needs the capability using either a toolbox approach or a domain-specific module approach. While these approaches have the advantage of side-stepping the difficult problem of determining sufficiency, they leave the larger problem unaddressed.

By presenting an architecture for general intelligence as a unified theory of cognition, one can bring additional knowledge to bear on the analysis of sufficiency. A working model - the human brain - is certainly sufficient to display general intelligence. The assumption is that one should push the limits of the architecture to produce a capability before building some domain-specific or problem-specific tool to overcome the difficulty. Additionally, the set of data represented by experiments in human cognition provide a measure against which one can measure performance, from which one can gain inspiration and and insight for further architectural revisions.


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