Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning

5 June 2024

Prasant Mohapatra

Papers citing "Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning"

29 / 29 papers shown

Title
Multi-agent Auto-Bidding with Latent Graph Diffusion Models Dom Huh P. Mohapatra DiffM AI4CE 94 0 0 04 Mar 2025
Efficient Multi-agent Reinforcement Learning by Planning Qihan Liu Jianing Ye Xiaoteng Ma Jun Yang Bin Liang Chongjie Zhang 67 6 0 20 May 2024
DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing Vint Lee Pieter Abbeel Youngwoon Lee 70 6 0 02 Nov 2023
Deep Latent State Space Models for Time-Series Generation Linqi Zhou Michael Poli Winnie Xu Stefano Massaroli Stefano Ermon BDL AI4TS 71 37 0 24 Dec 2022
Understanding Self-Predictive Learning for Reinforcement Learning Yunhao Tang Z. Guo Pierre Harvey Richemond Bernardo Avila-Pires Yash Chandak ... S. Thakoor Will Dabney Bilal Piot Daniele Calandriello Michal Valko SSL 106 30 0 06 Dec 2022
Towards a Standardised Performance Evaluation Protocol for Cooperative MARL R. Gorsane Omayma Mahjoub Ruan de Kock Roland Dubb Siddarth S. Singh Arnu Pretorius OffRL 78 50 0 21 Sep 2022
Sample-Efficient Multi-Agent Reinforcement Learning with Demonstrations for Flocking Control Yunbo Qiu Yuzhu Zhan Yue Jin Jian Wang Xudong Zhang 69 6 0 17 Sep 2022
VMAS: A Vectorized Multi-Agent Simulator for Collective Robot Learning Matteo Bettini Ryan Kortvelesy J. Blumenkamp Amanda Prorok 58 41 0 07 Jul 2022
Multi-Agent Reinforcement Learning is a Sequence Modeling Problem Muning Wen J. Kuba Runji Lin Weinan Zhang Ying Wen Jun Wang Yaodong Yang 96 188 0 30 May 2022
Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning J. Kuba Ruiqing Chen Munning Wen Ying Wen Fanglei Sun Jun Wang Yaodong Yang 112 245 0 23 Sep 2021
Pretraining Representations for Data-Efficient Reinforcement Learning Max Schwarzer Nitarshan Rajkumar Michael Noukhovitch Ankesh Anand Laurent Charlin Devon Hjelm Philip Bachman Aaron Courville OffRL 103 118 0 09 Jun 2021
MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale Dmitry Kalashnikov Jacob Varley Yevgen Chebotar Benjamin Swanson Rico Jonschkowski Chelsea Finn Sergey Levine Karol Hausman OffRL 116 280 0 16 Apr 2021
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games Chao Yu Akash Velu Eugene Vinitsky Jiaxuan Gao Yu Wang Alexandre M. Bayen Yi Wu OffRL 158 1,272 0 02 Mar 2021
Approximate information state for approximate planning and reinforcement learning in partially observed systems Jayakumar Subramanian Amit Sinha Raihan Seraj Aditya Mahajan 147 86 0 17 Oct 2020
Decoupling Representation Learning from Reinforcement Learning Adam Stooke Kimin Lee Pieter Abbeel Michael Laskin SSL DRL 367 345 0 14 Sep 2020
Phasic Policy Gradient K. Cobbe Jacob Hilton Oleg Klimov John Schulman OffRL 65 159 0 09 Sep 2020
Data-Efficient Reinforcement Learning with Self-Predictive Representations Max Schwarzer Ankesh Anand Rishab Goel R. Devon Hjelm Aaron Courville Philip Bachman 101 321 0 12 Jul 2020
Bootstrap your own latent: A new approach to self-supervised Learning Jean-Bastien Grill Florian Strub Florent Altché Corentin Tallec Pierre Harvey Richemond ... M. G. Azar Bilal Piot Koray Kavukcuoglu Rémi Munos Michal Valko SSL 401 6,844 0 13 Jun 2020
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning Z. Guo Bernardo Avila-Pires Bilal Piot Jean-Bastien Grill Florent Altché Rémi Munos M. G. Azar BDL DRL SSL 180 143 0 30 Apr 2020
CURL: Contrastive Unsupervised Representations for Reinforcement Learning A. Srinivas Michael Laskin Pieter Abbeel SSL DRL OffRL 108 1,092 0 08 Apr 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 503 3,444 0 09 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 390 18,897 0 13 Feb 2020
Dream to Control: Learning Behaviors by Latent Imagination Danijar Hafner Timothy Lillicrap Jimmy Ba Mohammad Norouzi VLM 135 1,374 0 03 Dec 2019
How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments Cédric Colas Olivier Sigaud Pierre-Yves Oudeyer 45 93 0 21 Jun 2018
Addressing Function Approximation Error in Actor-Critic Methods Scott Fujimoto H. V. Hoof David Meger OffRL 193 5,218 0 26 Feb 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor Tuomas Haarnoja Aurick Zhou Pieter Abbeel Sergey Levine 317 8,420 0 04 Jan 2018
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments Ryan J. Lowe Yi Wu Aviv Tamar J. Harb Pieter Abbeel Igor Mordatch 162 4,509 0 07 Jun 2017
Reinforcement Learning with Unsupervised Auxiliary Tasks Max Jaderberg Volodymyr Mnih Wojciech M. Czarnecki Tom Schaul Joel Z Leibo David Silver Koray Kavukcuoglu SSL 111 1,229 0 16 Nov 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 863 9,353 0 06 Jun 2015