The Multi-Agent Path Finding (MAPF) problem aims at finding non-conflicting paths for multiple agents from their respective sources to destinations. This problem arises in multiple real-life situations, including robot motion planning and airspace assignment for unmanned aerial vehicle movement. The problem is computationally expensive, and adding to it, the agents are rational and can misreport their private information. In this paper, we study both variants of the problem under the realm of fairness. For the non-rational agents, we propose a heuristic solution for this problem. Considering the agents are rational, we develop a mechanism and demonstrate that it is a dominant strategy, incentive compatible, and individually rational. We employ various solution methodologies to highlight the effectiveness and efficiency of the proposed solution approaches.

翻译：多智能体路径规划（MAPF）问题旨在为多个智能体寻找从各自起点到终点的无冲突路径。该问题出现在多种现实场景中，包括机器人运动规划与无人机空域分配。该问题计算复杂度高，且由于智能体具有理性特征，可能虚报其私有信息。本文在公平性框架下研究该问题的两种变体。针对非理性智能体，我们提出了一种启发式解决方案。对于理性智能体，我们设计了一种机制并证明其具有占优策略、激励相容及个体理性特征。我们采用多种求解方法验证了所提解决方案的有效性与效率。