The application of Situation-Sensitive Reinforcement Learning to a collaborative task with an agent dynamically changing its intention

Abstract

Cooperation of each participating agent is necessary in many multi-agent tasks: e.g., playing football, carrying a large table, etc. In cooperative tasks, an agent has to estimate the other agent's intention by watching how state variables change. In this paper, we describe a Situation-Sensitive Reinforcement Learning (SSRL), which enables an agent to notice the other agent's change in his/her intention and learn adequate behaviors.