Problem Solving Methods In Artificial Intelligence

Problem Solving Methods In Artificial Intelligence-50
Problem solving in psychology refers to the process of finding solutions to problems encountered in life.Solutions to these problems are usually situation- or context-specific.Formal logic is concerned with such issues as validity, truth, inference, argumentation and proof.

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However, already in 1958, John Mc Carthy proposed the advice taker, to represent information in formal logic and to derive answers to questions using automated theorem-proving.

A important step in this direction was made by Cordell Green in 1969, using a resolution theorem prover for question-answering and for such other applications in artificial intelligence as robot planning.

Rehabilitation psychologists studying individuals with frontal lobe injuries have found that deficits in emotional control and reasoning can be remediated with effective rehabilitation and could improve the capacity of injured persons to resolve everyday problems.

Interpersonal everyday problem solving is dependent upon the individual personal motivational and contextual components.

The resolution theorem-prover used by Cordell Green bore little resemblance to human problem solving methods.

In response to criticism of his approach, emanating from researchers at MIT, Robert Kowalski developed logic programming and SLD resolution, Problem solving is used when products or processes fail, so corrective action can be taken to prevent further failures.

The term problem solving means slightly different things depending on the discipline.

For instance, it is a mental process in psychology and a computerized process in computer science.

In these disciplines, problem solving is part of a larger process that encompasses problem determination, de-duplication, analysis, diagnosis, repair, and other steps.

Other problem solving tools are linear and nonlinear programming, queuing systems, and simulation.

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