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- 5Planning
- 1Action Elimination
- 1Active learning
- 1Actor-critic methods
- 1Bias-variance tradeoff
- 2Müller, Martin
- 2Nakhost, Hootan
- 2Valenzano, Richard
- 1Hoffman, Joerg
- 1Mueller, Martin
- 1Schaeffer, Jonathan
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Action Elimination and Plan Neighborhood Graph Search: Two Algorithms for Plan Improvement - Extended Version
Download2010
Nakhost, Hootan, Müller, Martin
Technical report TR10-01. Compared to optimal planners, satisficing planners can solve much harder problems but may produce overly costly and long plans. Plan quality for satisficing planners has become increasingly important. The most recent planning competition IPC-2008 used the cost of the...
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2013
Sturtevant, Nathan R., Valenzano, Richard, Schaeffer, Jonathan
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...
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2013
Valenzano, Richard, Müller, Martin, Xie, Fan
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...
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2010
Mueller, Martin, Hoffman, Joerg, Nakhost, Hootan
Technical report TR10-02. A ubiquitous feature of planning problems -- problems involving the automatic generation of action sequences for attaining a given goal -- is the need to economize limited resources such as fuel or money. While heuristic search, mostly based on standard algorithms such...