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What is Generate-and-Test Procedure

Chapter 277
Encyclopedia of Information Science and Technology, Second Edition
Is a common method of search, used in AI and other applications, in which possible solutions are generated systematically and evaluated until a suitable solution is found. For example, a game-playing program might generate possible moves, which are evaluated in terms of their likelihood of leading to a win. The greatest weakness of generate-and-test procedures is combinatorial explosion, which refers to the exponential increase of the number of possible solutions of increasing complexity (e.g., the number of moves that a game-playing program looks forward).
Published in Chapter:
History of Artificial Intelligence Before Computers
Bruce MacLennan (University of Tennessee, USA)
Copyright: © 2009 |Pages: 6
DOI: 10.4018/978-1-60566-026-4.ch277
Abstract
The history of artificial intelligence (AI) is commonly supposed to begin with Turing’s (1950) discussions of machine intelligence, and to have been defined as a field at the 1956 Dartmouth Summer Research Project on Artificial Intelligence. However, the ideas on which AI is based, and in particular those on which symbolic AI (see below) is based, have a very long history in the Western intellectual tradition, dating back to ancient Greece (see also McCorduck, 2004). It is important for modern researchers to understand this history for it reflects problematic assumptions about the nature of knowledge and cognition: assumptions that can impede the progress of AI if accepted uncritically.
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