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Much of computer science involves designing completely automatic systems that will later solve some specific problem -- systems to accept input data and, in a reasonable amount of time, calculate the correct response or a correct-enough approximation.In addition, people in computer science spend a surprisingly large amount of human time finding and fixing problems in their programs -- debugging.
Finally a solution is selected to be implemented and verified.
Problems have a goal to be reached and how you get there depends upon problem orientation (problem-solving coping style and skills) and systematic analysis.
The process starts with problem finding and problem shaping, where the problem is discovered and simplified.
The next step is to generate possible solutions and evaluate them.
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.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.There are two different types of problems, ill-defined and well-defined: different approaches are used for each.Well-defined problems have specific goals and clear expected solutions, while ill-defined problems do not.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.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.It can also be applied to a product or process prior to an actual failure event—when a potential problem can be predicted and analyzed, and mitigation applied so the problem never occurs.Techniques such as failure mode and effects analysis can be used to proactively reduce the likelihood of problems occurring.