An iterative updating heuristic search strategy for groundwater contamination source identification based on an ACPSO–ELM surrogate system

Author(s):  
Han Wang ◽  
Wenxi Lu ◽  
Zhenbo Chang
Author(s):  
Ryo Kuroiwa ◽  
Alex Fukunaga

Although symbolic bidirectional search is successful in optimal classical planning, state-of-the-art satisficing planners do not use bidirectional search. Previous bidirectional search planners for satisficing planning behaved similarly to a trivial portfolio, which independently executes forward and backward search without the desired ``meet-in-the-middle'' behavior of bidirectional search where the forward and backward search frontiers intersect at some point relatively far from the forward and backward start states. In this paper, we propose Top-to-Top Bidirectional Search (TTBS), a new bidirectional search strategy with front-to-front heuristic evaluation. We show that TTBS strongly exhibits ``meet-in-the-middle'' behavior and can solve instances solved by neither forward nor backward search on a number of domains.


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