Communication between embodied AI agents has received increasing attention in
recent years. Despite its use, it is still unclear whether the learned
communication is interpretable and grounded in perception. To study the
grounding of emergent forms of communication, we first introduce the
collaborative multi-object navigation task CoMON. In this task, an oracle agent
has detailed environment information in the form of a map. It communicates with
a navigator agent that perceives the environment visually and is tasked to find
a sequence of goals. To succeed at the task, effective communication is
essential. CoMON hence serves as a basis to study different communication
mechanisms between heterogeneous agents, that is, agents with different
capabilities and roles. We study two common communication mechanisms and
analyze their communication patterns through an egocentric and spatial lens. We
show that the emergent communication can be grounded to the agent observations
and the spatial structure of the 3D environment. Video summary:
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本论文通过介绍一个协作的多物体导航任务 CoMON，并研究不同通信机制，分析它们的通信模式，证明了学习出来的通信可以落实于 Agent 观察和环境的 3D 结构。