Anytime algorithms for biobjective heuristic search
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Anytime algorithms for mining groups with maximum coverage
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
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This paper presents a heuristic-search algorithm called Memory-bounded Anytime Window A*(MAWA*), which is complete, anytime, and memory bounded. MAWA* uses the window-bounded anytime-search methodology of AWA* as the basic framework and combines it with the memory-bounded A* -like approach to handle restricted memory situations. Simple and efficient versions of MAWA* targeted for tree search have also been presented. Experimental results of the sliding-tile puzzle problem and the traveling-salesman problem show the significant advantages of the proposed algorithm over existing methods.