Abstract
When a certain problem cannot be solved directly, it is often possible to write a program to search for a solution. If the number of possibilities to be searched in order to find a solution is sufficiently small, the problem is trivial since the program can consider all possibilities. For an intellectually difficult problem, the number of possibilities to be searched is so large (sometimes infinite) that for all practical purposes there is no exhaustive procedure. For example, in most kinds of theorem-proving including predicate calculus, the number of possibilities to be searched is potentially infinite. In order to guarantee a perfect first move in checkers, the program would have to search through about 1040 possible games. In chess the number is about 10120.Even tremendous improvements in hardware would hardly dent tasks requiring the search of so many possibilities. It is much better to consider alternative ways of defining the search and modifying the search, that is, to consider heuristic search techniques. In general, a heuristic is a rule of thumb, strategy, method or trick used to improve the efficiency of a system which tries to discover the solutions of complex problems. Some heuristics are specific, that is, limited to one problem-solving domain, such as proving theorems in geometry. Other heuristics are general, that is, applicable to several domains. For example, the heuristic of “working backwards” is useful in many theorem-proving and problem-solving domains.
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Slagle, J.R. (1970). Heuristic Search Programs. In: Banerji, R.B., Mesarovic, M.D. (eds) Theoretical Approaches to Non-Numerical Problem Solving. Lecture Notes in Operations Research and Mathematical Systems, vol 28. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-99976-5_9
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