人とAI群が協働するチーム対戦の取組み

人間30 人vs 1 人のしっぽ鬼

抄録

Towards close collaboration between a human and a large number of AI systems, we propose to design an AI agent with two technical elements. The first is the use of a modeling approach that enables us to know what AI agents are trying to do. The second is the use of a multi-agent consensus building algorithm. A good combination of these two, a human and a group of AI agents were put together as one team. In this paper, we explain a configuration using a Behavior Tree and a Contract Net Protocol as a concrete example. In addition, we propose a method of applying reinforcement learning in which the intentions of the AI agents can be easily grasped by a human. The effectiveness and feasibility of this approach were evaluated with teams in a simulated Tail Tag game. Matches were held with up to 29 AI agents and 1 person on one team and 30 people on the other team. The results indicate that our approach works almost evenly with human-human collaboration by sharing roles between a human and AI swarm.