J. Bowen and G. Dozier. Constraint Satisfaction Using a Hybrid Evolutionary Hill-Climbing Algorithm That Performs Opportunistic Arc and Path Revision. Proceedings of the 13 National Conference on Artificial Intelligence and the 8 Innovative Applications of Artificial Intelligence, AAAI Press/MIT Press, August 1996, Portland, Oregon, pp. 326 - 331. Home/Search Document Not in Database Summary Related Articles Check |
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Using an Incomplete Version of Dynamic Backtracking for Graph.. - Prestwich (1998) (Correct)
....escape from local minima [11, 21] Another well known stochastic algorithm is GSAT [18] which was designed to apply to Boolean satisfaction problems but has been successfully applied to several other CSPs. Both systematic and stochastic algorithms may be augmented by various forms of learning [1, 6, 7, 8, 15, 19, 20]: accumulating knowledge during search to avoid revisiting points in the search space. Some stochastic algorithms accumulate sufficient knowledge to ensure completeness, in which case they may be thought of as unusually flexible systematic algorithms. A currently active area of research is the ....
J. Bowen, G. Dozier. Constraint Satisfaction Using A Hybrid Evolutionary Hill-Climbing Algorithm That Performs Opportunistic Arc and Path Revision. Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference 1, AAAI Press / The MIT Press, 1996.
A Comparison of Traditional and Simple Evolutionary.. - Williams, Jr., Dozier Self-citation (Dozier) (Correct)
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J. Bowen and G. Dozier. Constraint Satisfaction Using a Hybrid Evolutionary Hill-Climbing Algorithm That Performs Opportunistic Arc and Path Revision. Proceedings of the 13 National Conference on Artificial Intelligence and the 8 Innovative Applications of Artificial Intelligence, AAAI Press/MIT Press, August 1996, Portland, Oregon, pp. 326 - 331.
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