動的マルチエージェント経路探索手法に関する研究：レビュー、シミュレーション、および改良
On dynamic multi-agent pathfinding methods: review, simulations and modifications
動的環境下でのマルチエージェント経路探索（D-MAPF）について、6つの代表的なアルゴリズムを統一的に比較し、新しい手法A**を提案してその有効性を示した論文。
著者: Gabriel Fejziaj, Salama Hassona, Wieslaw Marszalek
分類: nlin.CD, cs.MA, cs.RO
原文アブストラクト
This paper presents a systematic study of pathfinding algorithms in the context of Dynamic Multi-Agent Pathfinding (D-MAPF), a setting that combines dynamic obstacles, partial observability, and inter-agent conflicts. We evaluate six representative algorithms: Dijkstra, D* Lite, Space-Time A*, WHCA*, M*, and a novel method denoted as A** within a unified simulation framework. The proposed A** algorithm introduces a template-based approach that decouples offline geometric path generation from online temporal adaptation. By precomputing multiple diverse candidate paths and dynamically reconnecting to them using space-time planning, A** improves solution quality in environments with frequent changes and limited sensing