Abstract
This chapter looks at some of the particular problems associated with the computational demands of AI. The frame problem is a serious pragmatic problem characteristic of AI and NL, in which we must consider tradeoffs in time and space efficiency relating to storage and recall of information. More generally, we consider the question of efficiency and just what can and cannot be achieved in a given time frame. This is contrasted with the intransigent problems for which no efficacious algorithm can guarantee a solution in any time frame. Heuristics may be used to trade a fast probable solution against the possibility of failure in both these cases.
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© 1989 Springer-Verlag London Limited
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Powers, D.M.W., Turk, C.C.R. (1989). Heuristics and Analytic Intransigence. In: Machine Learning of Natural Language. Springer, London. https://doi.org/10.1007/978-1-4471-1697-4_12
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DOI: https://doi.org/10.1007/978-1-4471-1697-4_12
Publisher Name: Springer, London
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