Saturated cost partitioning and post-hoc optimization are two powerful cost partitioning algorithms for optimal classical planning. The main idea of saturated cost partitioning is to give each considered heuristic only the fraction of remaining operator costs that it needs to prove its estimates. We show how to apply this idea to post-hoc optimization and obtain a heuristic that dominates the original both in theory and on the IPC benchmarks
Optimal cost partitioning of classical planning heuristics has been shown to lead to excellent heuri...
Many heuristics for cost-optimal planning are based on linear programming. We cover several interest...
In this paper we present greedy methods for selecting a subset of heuristic functions for guiding A*...
Saturated cost partitioning and post-hoc optimization are two powerful cost partitioning algorithms ...
Cost partitioning is a method for admissibly combining a set of admissible heuristic estimators by d...
In classical planning, cost partitioning is a method for admissibly combining a set of heuristic est...
Cost partitioning is a general and principled approach for constructing additive admissible heuristi...
Cost partitioning is a method for admissibly adding multiple heuristics for state-space search. Satu...
Heuristic search with an admissible heuristic is one of the most prominent approaches to solving cla...
Many recent planning heuristics are based on LP optimization. However, planning experts mostly use L...
The zipfile contains an extended version of the Fast Downward planning system (http://fast-downward....
Cost partitioning is a general method for admissibly summing up heuristic estimates for optimal stat...
Pattern databases are the foundation of some of the strongest admissible heuristics for optimal clas...
Cost partitioning admissibly combines the information from multiple heuristics for optimal state-spa...
Code The file seipp-et-al-aaai2021-code.zip contains an extended version of the Fast Downward plann...
Optimal cost partitioning of classical planning heuristics has been shown to lead to excellent heuri...
Many heuristics for cost-optimal planning are based on linear programming. We cover several interest...
In this paper we present greedy methods for selecting a subset of heuristic functions for guiding A*...
Saturated cost partitioning and post-hoc optimization are two powerful cost partitioning algorithms ...
Cost partitioning is a method for admissibly combining a set of admissible heuristic estimators by d...
In classical planning, cost partitioning is a method for admissibly combining a set of heuristic est...
Cost partitioning is a general and principled approach for constructing additive admissible heuristi...
Cost partitioning is a method for admissibly adding multiple heuristics for state-space search. Satu...
Heuristic search with an admissible heuristic is one of the most prominent approaches to solving cla...
Many recent planning heuristics are based on LP optimization. However, planning experts mostly use L...
The zipfile contains an extended version of the Fast Downward planning system (http://fast-downward....
Cost partitioning is a general method for admissibly summing up heuristic estimates for optimal stat...
Pattern databases are the foundation of some of the strongest admissible heuristics for optimal clas...
Cost partitioning admissibly combines the information from multiple heuristics for optimal state-spa...
Code The file seipp-et-al-aaai2021-code.zip contains an extended version of the Fast Downward plann...
Optimal cost partitioning of classical planning heuristics has been shown to lead to excellent heuri...
Many heuristics for cost-optimal planning are based on linear programming. We cover several interest...
In this paper we present greedy methods for selecting a subset of heuristic functions for guiding A*...