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Simultaneously searching with multiple algorithm settings: an alternative to parameter tuning for suboptimal single-agent searchDownload
Many single-agent search algorithms have parameters that need to be tuned. Although settings found by offline tuning will exhibit strong average performance, properly selecting parameter settings for each problem can result in substantially reduced search effort. We consider the use of...
Most of the satisficing planners which are based on heuristic search iteratively improve their solution quality through an anytime approach. Typically, the lowest-cost solution found so far is used to constrain the search. This avoids areas of the state space which cannot directly lead to lower...
While greedy best-first search (GBFS) is a popular algorithm for solving automated planning tasks, it can exhibit poor performance if the heuristic in use mistakenly identifies a region of the search space as promising. In such cases, the way the algorithm greedily trusts the heuristic can cause...