Research map / Multi-agent systems and games / Human-AI and goal-conditioned
Multi-Agent Path Finding for Large Agents
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 |
|---|---|---|---|
| add multiple mutually disjunctive constraints per CT expansion (SYM vs CBS) | CBS · 20x20 grid square agents | runtime (ms): 52,876 -> 903 | Helped |
| choose constraint sets by maximizing child costs with lookahead (MAX-2 vs SYM) (ablation) | MC-CBS · 20x20 grid square agents | runtime (ms): 116,613 -> 6,373 | Helped |
| symmetric instead of asymmetric constraint sets (ablation) | MC-CBS · 20x20 grid square agents | expanded CT nodes | Helped |
| increase lookahead depth from 0 to 2 (ablation) | MAX · 20x20 grid, k=5 | runtime (ms): 104,597.3 -> 51,225.3 | Helped |
| increase lookahead depth from 3 to 4 (ablation) | MAX · 20x20 grid, k=5 | runtime (ms): 49,273.0 -> 55,912.9 | Hurt |
| add weighted conflict-graph heuristics (ablation) | MAX-4 · 20x20 grid, 8 agents | runtime: -21.5% | Helped |
| add weighted conflict-graph heuristics (ablation) | MAX · 20x20 grid | success rate | No clear effect |
| add weighted conflict-graph heuristics (ablation) | MAX-1 · Swap50 3D roadmap, k=8 | runtime (ms): 10,570 -> 5,221 | Helped |
| MAX-2 instead of MDD-SAT | LA-MAPF solving · 20x20 grid, 5 min limit | success rate | Mixed |
Closest papers by meaning
- Improving Continuous-time Conflict Based Search (AAAI 2021 · similarity 0.93)
- Anytime Multi-Agent Path Finding via Machine Learning-Guided Large Neighborhood Search (AAAI 2022 · similarity 0.92)
- Windowed MAPF with Completeness Guarantees (AAAI 2025 · similarity 0.91)
- Decentralized Monte Carlo Tree Search for Partially Observable Multi-Agent Pathfinding (AAAI 2024 · similarity 0.91)
- Loosely Synchronized Rule-Based Planning for Multi-Agent Path Finding with Asynchronous Actions (AAAI 2025 · similarity 0.90)
- Anytime Multi-Agent Path Finding with an Adaptive Delay-Based Heuristic (AAAI 2025 · similarity 0.90)
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.