Landmarks for Numeric Planning Problems
Authors: Enrico Scala, Patrik Haslum, Daniele Magazzeni, Sylvie Thiébaux
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental evaluation compares the landmark heuristics with the hybrid ˆhrmax hbd heuristic [Scala et al., 2016a], which is, to our knowledge, the only existing admissible heuristic for cost-optimal numeric planning. We apply the heuristics in a standard forward state space planner using A , so as to minimise any noise in the evaluation. The cost-partitioning problem is solved with CPLEX 12.63. Ties are broken preferring higher g-values. All heuristics are computed on a per-state basis.5 The evaluation is done over four numeric, non-temporal domains that have featured in the International Planning Competition6, the SAILING and FARMLAND domains from our earlier paper [Scala et al., 2016a], and the COUNTERS and GARDENING domains by Frances & Geffner [2015]. ... Table 1 shows a summary of the results. |
| Researcher Affiliation | Academia | The Australian National University, Canberra (AUS) King s College London, London, WC2R 2LS |
| Pseudocode | No | The paper does not contain any structured pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | Yes | The implementation is part of the ENHSP planning system, open sourced at https://bitbucket.org/enricode/the-enhsp-planner. |
| Open Datasets | Yes | The evaluation is done over four numeric, non-temporal domains that have featured in the International Planning Competition6, the SAILING and FARMLAND domains from our earlier paper [Scala et al., 2016a], and the COUNTERS and GARDENING domains by Frances & Geffner [2015]. |
| Dataset Splits | No | The paper describes evaluation on various planning domains and instances, but it does not specify training, validation, or test dataset splits in the conventional sense of machine learning. |
| Hardware Specification | Yes | Experiments have run on a Xeon E5-2660 V3 with 8G of RAM. |
| Software Dependencies | Yes | The cost-partitioning problem is solved with CPLEX 12.63. |
| Experiment Setup | Yes | We apply the heuristics in a standard forward state space planner using A , so as to minimise any noise in the evaluation. The cost-partitioning problem is solved with CPLEX 12.63. Ties are broken preferring higher g-values. All heuristics are computed on a per-state basis. |