相棒の行動から学ぶ：分散ロボットチームにおける役割分担
Learning from My Partner's Actions: Roles in Decentralized Robot Teams
各エージェントに探索・活用・通信などの役割を割り当てることで、明示的な通信なしに相手の行動意図を正しく解釈できる分散ロボットチームの手法を提案した。
著者: Dylan P. Losey, Mengxi Li, Jeannette Bohg, Dorsa Sadigh
分類: cs.RO, cs.AI
原文アブストラクト
When teams of robots collaborate to complete a task, communication is often necessary. Like humans, robot teammates should implicitly communicate through their actions: but interpreting our partner's actions is typically difficult, since a given action may have many different underlying reasons. Here we propose an alternate approach: instead of not being able to infer whether an action is due to exploration, exploitation, or communication, we define separate roles for each agent. Because each role defines a distinct reason for acting (e.g., only exploit, only communicate), teammates now correctly interpret the meaning behind their partner's actions. Our results suggest that leveraging and alternating roles leads to performance comparable to teams that explicitly exchange messages. You can find more images and videos of our experimental setups at http://ai.stanford.edu/blog/learning-from-partners/.
