G
Gabriele Röger
Researcher at University of Basel
Publications - 34
Citations - 840
Gabriele Röger is an academic researcher from University of Basel. The author has contributed to research in topics: Heuristic & Heuristics. The author has an hindex of 12, co-authored 31 publications receiving 719 citations. Previous affiliations of Gabriele Röger include University of Freiburg.
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Using the context-enhanced additive heuristic for temporal and numeric planning
TL;DR: Temporal Fast Downward (TFD) is presented, a planning system for temporal problems that is capable of finding low-makespan plans by performing a heuristic search in a temporal search space and outperforms all state-of-the-art temporal planning systems.
Proceedings Article
How good is almost perfect
Malte Helmert,Gabriele Röger +1 more
TL;DR: It is shown that for a number of common planning benchmark domains, including ones that admit optimal solution in polynomial time, general search algorithms such as A* must necessarily explore an exponential number of search nodes even under the optimistic assumption of almost perfect heuristic estimators, whose heuristic error is bounded by a small additive constant.
Proceedings Article
The more, the merrier: combining heuristic estimators for satisficing planning
Gabriele Röger,Malte Helmert +1 more
TL;DR: This work empirically examines several ways of exploiting the information of multiple heuristics in a satisficing best-first search algorithm, comparing their performance in terms of coverage, plan quality, speed, and search guidance.
Proceedings Article
LP-based heuristics for cost-optimal planning
TL;DR: With this new method of analysis, dominance of the recent LP-based state-equation heuristic over optimal cost partitioning on single-variable abstractions is shown and it is shown that the previously suggested extension of the state- EQUATION heuristic to exploit safe variables cannot lead to an improved heuristic estimate.
Proceedings Article
From non-negative to general operator cost partitioning
TL;DR: It is argued that this requirement for non-negative operator costs is not necessary and the benefit of using general cost partitioning is demonstrated, and it is shown that LP heuristics for operator-counting constraints are cost-partitionedHeuristics and that the state equation heuristic computes a cost partitioned over atomic projections.