论文标题
学习合作：多代理导航中的紧急沟通
Learning to cooperate: Emergent communication in multi-agent navigation
论文作者
论文摘要
已经研究了人造代理中的紧急沟通，以了解语言进化，并开发人工系统学会与人类进行交流。我们表明，在各种网格世界环境中执行合作导航任务的代理商学习了可解释的通信协议，使其能够有效地，并且在许多情况下可以最佳地解决该任务。对代理政策的分析表明，紧急信号在空间上群集在状态空间上，信号指的是特定位置和空间方向，例如“左”，“向上”或“左上室”。使用代理人种群，我们表明紧急协议具有基本的组成结构，因此具有自然语言的核心特性。
Emergent communication in artificial agents has been studied to understand language evolution, as well as to develop artificial systems that learn to communicate with humans. We show that agents performing a cooperative navigation task in various gridworld environments learn an interpretable communication protocol that enables them to efficiently, and in many cases, optimally, solve the task. An analysis of the agents' policies reveals that emergent signals spatially cluster the state space, with signals referring to specific locations and spatial directions such as "left", "up", or "upper left room". Using populations of agents, we show that the emergent protocol has basic compositional structure, thus exhibiting a core property of natural language.
