A New Framework for Multi-Agent Reinforcement Learning -- Centralized Training and Exploration with Decentralized Execution via Policy Distillation

21 October 2019

Papers citing "A New Framework for Multi-Agent Reinforcement Learning -- Centralized Training and Exploration with Decentralized Execution via Policy Distillation"

6 / 6 papers shown

Title
Curiosity-driven Exploration in Sparse-reward Multi-agent Reinforcement Learning Jiong Li Pratik Gajane 37 4 0 21 Feb 2023
Graph Neural Networks over the Air for Decentralized Tasks in Wireless Networks Zhan Gao Deniz Gunduz GNN 38 1 0 16 Feb 2023
Towards Semantic Communication Protocols: A Probabilistic Logic Perspective Sejin Seo Jihong Park Seung-Woo Ko Jinho Choi M. Bennis Seong-Lyun Kim 30 22 0 08 Jul 2022
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey Amjad Yousef Majid Serge Saaybi Tomas van Rietbergen Vincent François-Lavet R. V. Prasad Chris Verhoeven OffRL 60 54 0 28 Sep 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 36 92 0 14 Sep 2021
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning Jakob N. Foerster Nantas Nardelli Gregory Farquhar Triantafyllos Afouras Philip Torr Pushmeet Kohli Shimon Whiteson OffRL 119 595 0 28 Feb 2017