Research map / Learning theory and algorithms / Combinatorial and search optimization
Operator-Potential Heuristics for Symbolic Search
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use consistent operator-potential heuristics in symbolic forward search | Symbolic forward search · IPC optimal-track tasks, 1998–2018 | solved tasks: 173 more tasks | Helped |
| Use consistent operator-potential heuristics instead of blind bidirectional uniform-cost search | Symbolic search · IPC optimal-track tasks, 1998–2018 | solved tasks: 105 more tasks | Helped |
| Use symbolic search with A+I rather than explicit-state potential-heuristic A* | Potential heuristic A+I · IPC optimal-track tasks, 1998–2018 | solved tasks: 109 instances more | Helped |
| Optimize the heuristic over average states while enforcing maximum initial-state value, rather than only optimizing initial-state value (ablation) | Operator-potential symbolic search · IPC optimal-track tasks, 1998–2018 | solved tasks: 1 109 vs 996 | Helped |
| Use sampled-state optimization (S1k+I) instead of initial-state-only optimization (I) (ablation) | Operator-potential symbolic search · IPC optimal-track tasks, 1998–2018 | solved tasks: 1 081 vs 996 | Helped |
| Use mutex-approximated reachable-state optimization (M2+I) instead of initial-state-only optimization (I) (ablation) | Operator-potential symbolic search · IPC optimal-track tasks, 1998–2018 | solved tasks: 1 103 vs 996 | Helped |
| Use path-dependent operator potentials on the original task instead of consistent operator potentials on the transformed task (ablation) | Operator-potential symbolic search · IPC optimal-track tasks, 1998–2018 | coverage across domains | Hurt |
| Use floating-point potentials rounded down instead of integer operator potentials from the MIP (ablation) | Path-dependent operator-potential heuristic · IPC optimal-track tasks, 1998–2018 | solved tasks: 107 fewer tasks from 20 domains | Hurt |
| Transform planning tasks to transition normal form (ablation) | Operator-potential symbolic search · IPC optimal-track tasks, 1998–2018 | coverage | Hurt |
| Use operator-potential heuristics that induce heuristic-value partitions in symbolic search | Symbolic forward search · Commonly solved tasks | mean BDD nodes per expanded BDD | Helped |
| Use operator-potential heuristics instead of blind symbolic forward search | Symbolic forward search · Commonly solved tasks | number of expanded BDDs | Hurt |
| Use operator-potential heuristics instead of blind symbolic forward search | Symbolic forward search · Commonly solved tasks | sum of expanded BDD nodes | Helped |
Closest papers by meaning
- Symbolic Numeric Planning with Patterns (AAAI 2024 · similarity 0.87)
- Automatic Selection of Macro-Events for Heuristic-Search Temporal Planning (AAAI 2025 · similarity 0.85)
- Novelty vs. Potential Heuristics: A Comparison of Hardness Measures for Satisficing Planning (AAAI 2024 · similarity 0.84)
- SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling (NeurIPS 2024 · similarity 0.84)
- SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning (ICLR 2024 · similarity 0.84)
- Towards Practical Classical Planning Compilations of Numeric Planning (AAAI 2025 · similarity 0.84)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.