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Cognitive Science 7: Applying the Symbolic Paradigm


This chapter offers three examples of how physical symbol systems are actualized in specific information processing problems. The first application is to expert systems. The ID3 machine learning algorithm that constructs a decision tree based on information provided. Based on set calculations and a process that follows the heuristic search hypothesis (transforming complex symbol structures into a solution structure) to allow for advanced, and highly effective decision making that can outperform experts.

WHISPER is an application of the physical symbol system to a simulated visual environment. It is the application of the theory to a less intuitive area. So far, the applications have been language based, but WHISPER shows that this need not be the case.

Up until this point, all the applications have been in simulated environments. SHAKEY is the first application to a physical environment. Using similar rules, a robot is able to follow complex orders (which can be reduced to transforming complex symbol structures in to a solution structure, the basis for the physical symbol system hypothesis).

The above appear to be basic proofs of concept, although no one would argue that they are what goes on in human cognition. It does show that very simple algorithmic processes can account for complex decision making behaviors. A step in the right direction.

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