Intrinsic Motivated Multi-Agent Communication

Chuxiong Sun (The Institute of Software, Chinese Academy of Sciences), Bo Wu (The Institute of Software, Chinese Academy of Sciences), Rui Wang (The Institute of Software, Chinese Academy of Sciences), Xiaohui Hu (The Institute of Software, Chinese Academy of Sciences), Xiaoya Yang (The Institute of Software, Chinese Academy of Sciences), Cong Cong (The Institute of Software, Chinese Academy of Sciences)

Abstract

Efficient communication is a promising way to achieve cooperation among agents in many real-world scenarios. However, aimless and motiveless information sharing may not work or even degrade the cooperative performance. Typically, the multi-agent communication behaviors are motivated by extrinsic rewards from environment. We conclude the mechanism as 'Communicate what rewards you'. In this work, we present a novel communication mechanism called Intrinsic Motivated Multi-Agent Communication (IMMAC). Our key insight can be summarized as 'Communicate what surprises you'. Concretely, we use an observation-dependent intrinsic value to represent the importance of observed information. Then a gating mechanism and an attentional mechanism based on intrinsic values are designed to control communication. By encouraging agent to communicate and focus on the observations with uncertain and important information, our algorithm achieves superior communication efficiency and cooperative performance. We evaluate IMMAC on a variety of challenging tasks, and demonstrate that intrinsic values are sufficient to drive efficient communication behaviors. Moreover, we found that the combination of intrinsic values and extrinsic values can further improve the communication efficiency. Consequently, intrinsic motivation is a promising way to control communication and it is capable of being a good complement to the existing extrinsic motivated communication methods.