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by Pascal Nicolas, Frdric Saubion, Igor Stphan
In Proc. 8th European Conf. Artificial Intelligence (JELIA
http://www.info.univ-angers.fr/pub/pn/Publi/jelia02.ps.gz
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Abstract:
Abstract. Answer Set Programming is a very convenient framework to represent various problems issued from Articial Intelligence (nonmonotonic reasoning, planning, diagnosis...). Furthermore, it can be used to neatly encode combinatorial problems. In all cases, the solutions are obtained as sets of literals: the Answer Sets. Ant Colony Optimization is a general metaheuristics that has been already successfully used to solve hard combinatorial problems (traveling salesman problem, graph coloring, quadratic assignment...). It is based on the collective behavior of articial ants exploring a graph and exchanging pieces of information by means of pheromone traces. The purpose of this work is to show how Ant Colony Optimization can be used to compute an answer set of a logic program. 1
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