Demo: A multi-agent communication reinforcement learning Cooperative Detection System

Author:

Gao Hongye1ORCID,Shi Yichen2ORCID,Rao Weixiong2ORCID,Ma Qiongmin3ORCID

Affiliation:

1. Tongji University,, Shanghai, China

2. Tongji University, Shanghai, China

3. National Key Laboratory for Complex Systems Simulation, Beijing, China

Publisher

ACM

Reference14 articles.

1. Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba. 2016. OpenAI Gym. CoRR abs/1606.01540 (2016). arXiv:1606.01540 http://arxiv.org/abs/1606.01540

2. Robots for Environmental Monitoring: Significant Advancements and Applications

3. Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, and Shimon Whiteson. 2016. Learning to Communicate with Deep Multi-Agent Reinforcement Learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5--10, 2016, Barcelona, Spain, Daniel D. Lee, Masashi Sugiyama, Ulrike von Luxburg, Isabelle Guyon, and Roman Garnett (Eds.). 2137--2145. https://proceedings.neurips.cc/paper/2016/hash/c7635bfd99248a2cdef8249ef7bfbef4-Abstract.html

4. Scalable Communication for Mobile Multi-Agent Cooperative Detection

5. Eric Jang, Shixiang Gu, and Ben Poole. 2017. Categorical Reparameterization with Gumbel-Softmax. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24--26, 2017, Conference Track Proceedings. OpenReview.net. https://openreview.net/forum?id=rkE3y85ee

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