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Features of Problem-Solving Method using Computation Model CCM, based on Production Rules and Local Evaluation Functions

Kanada, Y., SWoPP '93 (SIG Notes of Artificial Intelligence), Information Processing Society of Japan, 93-AI-89-2, 11-20, 1993, Published by IPSJ.

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Abstract: Problem-solving, such as constraint satisfaction or optimization, can be viewed as solution search. Conventional solution search methods in Artificial Intelligence and Operations Research are based on exhaustive and systematic search on tree-structured search space using backtrack. The author proposed a computation model called CCM (Chemical Casting Model), which is based on production rules and local evaluation functions that work in a decentralized and parallel manner, in recent papers. Solution search using CCM can be regarded as random walk on search space, biased by evaluation functions. Several features of this method are that it searches on strongly-connected graphs, that reversible and symmetric rules are used, and that the strength of bias and the locality of rules can be changed by adding or removing so-called catalysts in rules or by composing rules.

Introduction to this research theme: CCM: Chemical-Computation Model

Keywords: CCM, Constraint satisfaction problem, Emergent computation, Randomized computation, Randomized problem solving, Rule-based computation, Rule-based problem solving, Local information, Localized computation, Local evaluation function

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