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The ability to understand what the goal of the problem is, and what rules could be applied, represents the key to solving the problem.
One such component is the emotional valence of "real-world" problems and it can either impede or aid problem-solving performance.
Researchers have focused on the role of emotions in problem solving , In conceptualization, human problem solving consists of two related processes: problem orientation and the motivational/attitudinal/affective approach to problematic situations and problem-solving skills.
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.
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.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.Well-defined problems allow for more initial planning than ill-defined problems.Solving problems sometimes involves dealing with pragmatics, the way that context contributes to meaning, and semantics, the interpretation of the problem.The use of computers to prove mathematical theorems using formal logic emerged as the field of automated theorem proving in the 1950s. Shaw, as well as algorithmic methods, such as the resolution principle developed by John Alan Robinson.It included the use of heuristic methods designed to simulate human problem solving, as in the Logic Theory Machine, developed by Allen Newell, Herbert A. In addition to its use for finding proofs of mathematical theorems, automated theorem-proving has also been used for program verification in computer science.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.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.