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1 2020

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Multi agent deep learning with cooperative communication

Simões David, Lau Nuno, Reis Luís Paulo

Journal of Artificial Intelligence and Soft Computing Research

2020

Vol. 10, No. 3

189--207

We consider the problem of multi agents cooperating in a partially-observable environment. Agents must learn to coordinate and share relevant information to solve the tasks successfully. This article describes Asynchronous Advantage Actor-Critic with Communication (A3C2), an end-to-end differentiable approach where agents learn policies and communication protocols simultaneously. A3C2 uses a centralized learning, distributed execution paradigm, supports independent agents, dynamic team sizes, partiallyobservable environments, and noisy communications. We compare and show that A3C2 outperforms other state-of-the-art proposals in multiple environments.