Feasibility Study: Moving Non-Homogeneous Teams in Congested Video Game Environments
This addresses pathfinding for diverse agent teams in video games, but appears incremental as it applies existing MAPF methods to a new context.
The paper tackled the problem of moving non-homogeneous teams in congested video game environments by applying multi-agent path finding (MAPF) algorithms from artificial intelligence, demonstrating their usefulness without specifying concrete numerical results.
Multi-agent path finding (MAPF) is a well-studied problem in artificial intelligence, where one needs to find collision-free paths for agents with given start and goal locations. In video games, agents of different types often form teams. In this paper, we demonstrate the usefulness of MAPF algorithms from artificial intelligence for moving such non-homogeneous teams in congested video game environments.