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This page describes the various merge strategies supported by the planner. |
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| * Silvan Sievers, Martin Wehrle, and Malte Helmert.<<BR>> | * Silvan Sievers, Martin Wehrle and Malte Helmert.<<BR>> |
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| [[http://ai.cs.unibas.ch/papers/helmert-et-al-icaps2007.pdf|Flexible Abstraction Heuristics for Optimal Sequential Planning]]<<BR>> | [[http://ai.cs.unibas.ch/papers/helmert-et-al-icaps2007.pdf|Flexible Abstraction Heuristics for Optimal Sequential Planning]].<<BR>> |
This page describes the various merge strategies supported by the planner.
Merge strategy DFP
This merge strategy implements the algorithm originally described in the paper "Directed model checking with distance-preserving abstractions" by Draeger, Finkbeiner and Podelski (SPIN 2006), adapted to planning in the following paper:
Silvan Sievers, Martin Wehrle and Malte Helmert.
Generalized Label Reduction for Merge-and-Shrink Heuristics.
In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI 2014), pp. 2358-2366. AAAI Press 2014.
merge_dfp()
Linear merge strategies
This merge strategy implements several linear merge orders, which are described in the paper:
Malte Helmert, Patrik Haslum and Joerg Hoffmann.
Flexible Abstraction Heuristics for Optimal Sequential Planning.
In Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling (ICAPS 2007), pp. 176-183. 2007.
merge_linear(variable_order=CG_GOAL_LEVEL)
variable_order ({CG_GOAL_LEVEL, CG_GOAL_RANDOM, GOAL_CG_LEVEL, RANDOM, LEVEL, REVERSE_LEVEL}): the order in which atomic transition systems are merged