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Experimental evaluation of pheromone models in ACOPlan. (English) Zbl 1253.68294
Summary: In this paper the system ACOPlan for planning with non uniform action cost is introduced and analyzed. ACOPlan is a planner based on the ant colony optimization framework, in which a colony of planning ants searches for near optimal solution plans with respect to an overall plan cost metric. This approach is motivated by the strong similarity between the process used by artificial ants to build solutions and the methods used by state-based planners to search solution plans. Planning ants perform a stochastic and heuristic based search by interacting through a pheromone model. The proposed heuristic and pheromone models are presented and compared through systematic experiments on benchmark planning domains. Experiments are also provided to compare the quality of ACOPlan solution plans with respect to state of the art satisficing planners. The analysis of the results confirm the good performance of the action-action pheromone model and points out the promising performance of the novel fuzzy-level-action pheromone model. The analysis also suggests general principles for designing performant pheromone models for planning and further extensions of ACOPlan to other optimization models.
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
68T05 Learning and adaptive systems in artificial intelligence
68W20 Randomized algorithms
68W25 Approximation algorithms
Walksat; SAPA; Graphplan; LPG
Full Text: DOI
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