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Phase transitions and the search problem
Artificial Intelligence 81 (1-2):1-15 (1996)
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Citations of this work
Distributed stochastic search and distributed breakout: properties, comparison and applications to constraint optimization problems in sensor networks.Weixiong Zhang, Guandong Wang, Zhao Xing & Lars Wittenburg - 2005 - Artificial Intelligence 161 (1-2):55-87.
On market-inspired approaches to propositional satisfiability.William E. Walsh, Makoto Yokoo, Katsutoshi Hirayama & Michael P. Wellman - 2003 - Artificial Intelligence 144 (1-2):125-156.
Configuration landscape analysis and backbone guided local search.Weixiong Zhang - 2004 - Artificial Intelligence 158 (1):1-26.
Phase transitions in random Potts systems and the community detection problem: spin-glass type and dynamic perspectives.Dandan Hu, Peter Ronhovde & Zohar Nussinov - 2012 - Philosophical Magazine 92 (4):406-445.
Problem difficulty for tabu search in job-shop scheduling.Jean-Paul Watson, J. Christopher Beck, Adele E. Howe & L. Darrell Whitley - 2003 - Artificial Intelligence 143 (2):189-217.
References found in this work
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems.Steven Minton, Mark D. Johnston, Andrew B. Philips & Philip Laird - 1992 - Artificial Intelligence 58 (1-3):161-205.
Phase transitions in artificial intelligence systems.Bernardo A. Huberman & Tad Hogg - 1987 - Artificial Intelligence 33 (2):155-171.
Exploiting the deep structure of constraint problems.Colin P. Williams & Tad Hogg - 1994 - Artificial Intelligence 70 (1-2):73-117.
An empirical study of phase transitions in binary constraint satisfaction problems.Patrick Prosser - 1996 - Artificial Intelligence 81 (1-2):81-109.
The hardest constraint problems: A double phase transition.Tad Hogg & Colin P. Williams - 1994 - Artificial Intelligence 69 (1-2):359-377.
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