On the Completeness of Conflict-Based Search: Temporally-Relative Duplicate Pruning
This addresses a theoretical loophole for researchers and practitioners in multi-agent pathfinding, making CBS complete without major runtime penalties, though it is an incremental improvement.
The paper tackles the incompleteness of the Conflict-Based Search (CBS) algorithm for multi-agent pathfinding by introducing Temporally-Relative Duplicate Pruning (TRDP), a technique that detects and removes duplicate states to ensure termination, with empirical results showing no significant runtime impact in most cases and performance improvements in some instances.
Conflict-Based Search (CBS) algorithm for the multi-agent pathfinding (MAPF) problem is that it is incomplete for problems which have no solution; if no mitigating procedure is run in parallel, CBS will run forever when given an unsolvable problem instance. In this work, we introduce Temporally-Relative Duplicate Pruning (TRDP), a technique for duplicate detection and removal in both classic and continuous-time MAPF domains. TRDP is a simple procedure which closes the long-standing theoretic loophole of incompleteness for CBS by detecting and avoiding the expansion of duplicate states. TRDP is shown both theoretically and empirically to ensure termination without a significant impact on runtime in the majority of problem instances. In certain cases, TRDP is shown to increase performance significantly