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Pommerman: A Multi-Agent Playground
v1v2 (latest)

Pommerman: A Multi-Agent Playground

19 September 2018
Cinjon Resnick
W. Eldridge
David R Ha
D. Britz
Jakob N. Foerster
Julian Togelius
Dong Wang
Joan Bruna
    LLMAG
ArXiv (abs)PDFHTML

Papers citing "Pommerman: A Multi-Agent Playground"

48 / 48 papers shown
MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning
MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning
Tristan Tomilin
Luka van den Boogaard
Samuel Garcin
Bram Grooten
Meng Fang
Yali Du
Mykola Pechenizkiy
OffRL
217
0
0
17 Jun 2025
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement Learning
Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement Learning
Weiqiang Jin
Hongyang Du
Guizhong Liu
Dong In Kim
190
0
0
09 Jun 2025
Multi-Agent Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach
Multi-Agent Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach
Nhat-Minh Huynh
Hoang-Giang Cao
I-Chen Wu
244
5
0
30 Jun 2024
Embodied LLM Agents Learn to Cooperate in Organized Teams
Embodied LLM Agents Learn to Cooperate in Organized Teams
Xudong Guo
Kaixuan Huang
Jiale Liu
Wenhui Fan
Natalia Vélez
Qingyun Wu
Huazheng Wang
Thomas L. Griffiths
Mengdi Wang
LM&RoLLMAG
355
68
0
19 Mar 2024
Checkmating One, by Using Many: Combining Mixture of Experts with MCTS to Improve in Chess
Checkmating One, by Using Many: Combining Mixture of Experts with MCTS to Improve in Chess
Felix Helfenstein
Johannes Czech
Johannes Czech
Max Eisel
Kristian Kersting
257
3
0
30 Jan 2024
The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent
  Competition with Specialization and Trade
The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and TradeNeural Information Processing Systems (NeurIPS), 2023
Enhong Liu
Joseph Suárez
Chenhui You
Bo Wu
Bingcheng Chen
...
Yuejia Huang
Kun Zhang
Hanhui Yang
Shi-bao Tang
Phillip Isola
79
0
0
07 Nov 2023
Building Cooperative Embodied Agents Modularly with Large Language Models
Building Cooperative Embodied Agents Modularly with Large Language ModelsInternational Conference on Learning Representations (ICLR), 2023
Hongxin Zhang
Weihua Du
Jiaming Shan
Qinhong Zhou
Yilun Du
J. Tenenbaum
Tianmin Shu
Chuang Gan
LLMAGLM&Ro
550
259
0
05 Jul 2023
More Like Real World Game Challenge for Partially Observable Multi-Agent
  Cooperation
More Like Real World Game Challenge for Partially Observable Multi-Agent Cooperation
Meng Yao
Xueou Feng
Qiyue Yin
226
0
0
15 May 2023
Games for Artificial Intelligence Research: A Review and Perspectives
Games for Artificial Intelligence Research: A Review and PerspectivesIEEE Transactions on Artificial Intelligence (IEEE TAI), 2023
Chengpeng Hu
Yunlong Zhao
Ziqi Wang
Haocheng Du
Jialin Liu
AI4CE
269
20
0
26 Apr 2023
Learning from Multiple Independent Advisors in Multi-agent Reinforcement
  Learning
Learning from Multiple Independent Advisors in Multi-agent Reinforcement LearningAdaptive Agents and Multi-Agent Systems (AAMAS), 2023
Sriram Ganapathi Subramanian
Matthew E. Taylor
Kate Larson
Mark Crowley
145
1
0
26 Jan 2023
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement
  Learning
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2022
Benjamin Ellis
Jonathan Cook
S. Moalla
Mikayel Samvelyan
Mingfei Sun
Anuj Mahajan
Jakob N. Foerster
Shimon Whiteson
443
133
0
14 Dec 2022
Efficient Exploration in Resource-Restricted Reinforcement Learning
Efficient Exploration in Resource-Restricted Reinforcement LearningAAAI Conference on Artificial Intelligence (AAAI), 2022
Zhihai Wang
Taoxing Pan
Qi Zhou
Jie Wang
OffRL
127
13
0
14 Dec 2022
Decision-making with Speculative Opponent Models
Decision-making with Speculative Opponent ModelsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Jing-rong Sun
Shuo Chen
Cong Zhang
Yining Ma
Jie Zhang
236
2
0
22 Nov 2022
MARLlib: A Scalable and Efficient Multi-agent Reinforcement Learning
  Library
MARLlib: A Scalable and Efficient Multi-agent Reinforcement Learning Library
Siyi Hu
Yifan Zhong
Minquan Gao
Weixun Wang
Hao Dong
Xiaodan Liang
Zhihui Li
Xiaojun Chang
Yaodong Yang
171
30
0
11 Oct 2022
VMAS: A Vectorized Multi-Agent Simulator for Collective Robot Learning
VMAS: A Vectorized Multi-Agent Simulator for Collective Robot LearningInternational Symposium on Distributed Autonomous Robotic Systems (DARS), 2022
Matteo Bettini
Ryan Kortvelesy
J. Blumenkamp
Amanda Prorok
238
62
0
07 Jul 2022
Self-Imitation Learning from Demonstrations
Self-Imitation Learning from Demonstrations
Georgiy Pshikhachev
Dmitry Ivanov
Vladimir Egorov
A. Shpilman
192
8
0
21 Mar 2022
Developing a Successful Bomberman Agent
Developing a Successful Bomberman AgentInternational Conference on Agents and Artificial Intelligence (ICAART), 2022
D. Kowalczyk
Jakub Kowalski
Hubert Obrzut
Michael Maras
Szymon Kosakowski
Radoslaw Miernik
218
1
0
17 Mar 2022
The Partially Observable Asynchronous Multi-Agent Cooperation Challenge
The Partially Observable Asynchronous Multi-Agent Cooperation Challenge
Meng Yao
Qiyue Yin
Jun Yang
Tongtong Yu
S. Shen
Junge Zhang
Bin Liang
Kaiqi Huang
151
5
0
07 Dec 2021
Collective Intelligence for Deep Learning: A Survey of Recent
  Developments
Collective Intelligence for Deep Learning: A Survey of Recent DevelopmentsCollective Intelligence (CI), 2021
David R Ha
Yu Tang
AI4CE
347
85
0
29 Nov 2021
Multi-Agent Advisor Q-Learning
Multi-Agent Advisor Q-Learning
Sriram Ganapathi Subramanian
Matthew E. Taylor
Kate Larson
Mark Crowley
OffRL
309
11
0
26 Oct 2021
The Neural MMO Platform for Massively Multiagent Research
The Neural MMO Platform for Massively Multiagent Research
Joseph Suárez
Yilun Du
Clare Zhu
Igor Mordatch
Phillip Isola
AI4CE
197
27
0
14 Oct 2021
Learning to Play Imperfect-Information Games by Imitating an Oracle
  Planner
Learning to Play Imperfect-Information Games by Imitating an Oracle PlannerIEEE Transactions on Games (IEEE Trans. Games), 2020
Rinu Boney
Alexander Ilin
Arno Solin
Jarno Seppänen
132
3
0
22 Dec 2020
Flatland-RL : Multi-Agent Reinforcement Learning on Trains
Flatland-RL : Multi-Agent Reinforcement Learning on Trains
Sharada Mohanty
Erik Nygren
Florian Laurent
Manuel Schneider
Christian Scheller
...
Christian Baumberger
Gereon Vienken
Irene Sturm
Guillaume Sartoretti
G. Spigler
OffRL
283
64
0
10 Dec 2020
TLeague: A Framework for Competitive Self-Play based Distributed
  Multi-Agent Reinforcement Learning
TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning
Yang Liu
Jiechao Xiong
Lei Han
Xinghai Sun
Shuxing Li
Jiawei Xu
Meng Fang
Zhengyou Zhang
OffRLLRM
296
20
0
25 Nov 2020
Sample Efficient Training in Multi-Agent Adversarial Games with Limited
  Teammate Communication
Sample Efficient Training in Multi-Agent Adversarial Games with Limited Teammate Communication
Hardik Meisheri
H. Khadilkar
LLMAG
166
2
0
01 Nov 2020
Watch-And-Help: A Challenge for Social Perception and Human-AI
  Collaboration
Watch-And-Help: A Challenge for Social Perception and Human-AI CollaborationInternational Conference on Learning Representations (ICLR), 2020
Xavier Puig
Tianmin Shu
Shuang Li
Zilin Wang
Yuan-Hong Liao
J. Tenenbaum
Sanja Fidler
Antonio Torralba
LM&Ro
335
155
0
19 Oct 2020
Pow-Wow: A Dataset and Study on Collaborative Communication in Pommerman
Pow-Wow: A Dataset and Study on Collaborative Communication in PommermanInternational Conference on Machine Learning (ICML), 2020
Takuma Yoneda
Matthew R. Walter
Jason Naradowsky
LLMAG
100
1
0
13 Sep 2020
Battlesnake Challenge: A Multi-agent Reinforcement Learning Playground
  with Human-in-the-loop
Battlesnake Challenge: A Multi-agent Reinforcement Learning Playground with Human-in-the-loop
Jonathan Chung
Anna Luo
Xavier Raffin
Scott Perry
OffRL
117
3
0
20 Jul 2020
Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in
  Cooperative Tasks
Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks
Georgios Papoudakis
Filippos Christianos
Lukas Schafer
Stefano V. Albrecht
OffRL
360
301
0
14 Jun 2020
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
Thomas W. Anthony
Tom Eccles
Andrea Tacchetti
János Kramár
I. Gemp
...
Richard Everett
Roman Werpachowski
Satinder Singh
T. Graepel
Yoram Bachrach
315
45
0
08 Jun 2020
Accelerating Training in Pommerman with Imitation and Reinforcement
  Learning
Accelerating Training in Pommerman with Imitation and Reinforcement Learning
Hardik Meisheri
Omkar Shelke
Richa Verma
H. Khadilkar
175
6
0
12 Nov 2019
On Hard Exploration for Reinforcement Learning: a Case Study in
  Pommerman
On Hard Exploration for Reinforcement Learning: a Case Study in PommermanArtificial Intelligence and Interactive Digital Entertainment Conference (AIIDE), 2019
Chao Gao
Bilal Kartal
Pablo Hernandez-Leal
Matthew E. Taylor
114
10
0
26 Jul 2019
Action Guidance with MCTS for Deep Reinforcement Learning
Action Guidance with MCTS for Deep Reinforcement LearningArtificial Intelligence and Interactive Digital Entertainment Conference (AIIDE), 2019
Bilal Kartal
Pablo Hernandez-Leal
Matthew E. Taylor
111
18
0
25 Jul 2019
Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning
Terminal Prediction as an Auxiliary Task for Deep Reinforcement LearningArtificial Intelligence and Interactive Digital Entertainment Conference (AIIDE), 2019
Bilal Kartal
Pablo Hernandez-Leal
Matthew E. Taylor
284
30
0
24 Jul 2019
Agent Modeling as Auxiliary Task for Deep Reinforcement Learning
Agent Modeling as Auxiliary Task for Deep Reinforcement LearningArtificial Intelligence and Interactive Digital Entertainment Conference (AIIDE), 2019
Pablo Hernandez-Leal
Bilal Kartal
Matthew E. Taylor
138
51
0
22 Jul 2019
Arena: a toolkit for Multi-Agent Reinforcement Learning
Arena: a toolkit for Multi-Agent Reinforcement Learning
Qing Wang
Jiechao Xiong
Lei Han
Meng Fang
Xinghai Sun
Zhuobin Zheng
Yang Liu
Zhengyou Zhang
140
4
0
20 Jul 2019
Evolutionary Reinforcement Learning for Sample-Efficient Multiagent
  Coordination
Evolutionary Reinforcement Learning for Sample-Efficient Multiagent CoordinationInternational Conference on Machine Learning (ICML), 2019
Shauharda Khadka
Somdeb Majumdar
Santiago Miret
Stephen McAleer
Kagan Tumer
259
66
0
18 Jun 2019
Learning Transferable Cooperative Behavior in Multi-Agent Teams
Learning Transferable Cooperative Behavior in Multi-Agent TeamsAdaptive Agents and Multi-Agent Systems (AAMAS), 2019
Akshat Agarwal
Sumit Kumar
Katia Sycara
AI4CE
194
138
0
04 Jun 2019
Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition
Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition
Chao Gao
Pablo Hernandez-Leal
Bilal Kartal
Matthew E. Taylor
118
18
0
20 Apr 2019
Safer Deep RL with Shallow MCTS: A Case Study in Pommerman
Safer Deep RL with Shallow MCTS: A Case Study in Pommerman
Bilal Kartal
Pablo Hernandez-Leal
Chao Gao
Matthew E. Taylor
OffRL
158
7
0
10 Apr 2019
Real-time tree search with pessimistic scenarios
Real-time tree search with pessimistic scenariosAsian Conference on Machine Learning (ACML), 2019
Takayuki Osogami
Toshihiro Takahashi
145
14
0
28 Feb 2019
The StarCraft Multi-Agent Challenge
The StarCraft Multi-Agent ChallengeAdaptive Agents and Multi-Agent Systems (AAMAS), 2019
Mikayel Samvelyan
Tabish Rashid
Christian Schroeder de Witt
Gregory Farquhar
Nantas Nardelli
Tim G. J. Rudner
Chia-Man Hung
Juil Sock
Jakob N. Foerster
Shimon Whiteson
710
1,125
0
11 Feb 2019
Obstacle Tower: A Generalization Challenge in Vision, Control, and
  Planning
Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning
Arthur Juliani
Ahmed Khalifa
Vincent-Pierre Berges
Jonathan Harper
Ervin Teng
Hunter Henry
A. Crespi
Julian Togelius
Danny Lange
280
148
0
04 Feb 2019
Competitive Experience Replay
Competitive Experience ReplayInternational Conference on Learning Representations (ICLR), 2019
Hao Liu
Alexander R. Trott
R. Socher
Caiming Xiong
OffRL
306
58
0
01 Feb 2019
Continual Match Based Training in Pommerman: Technical Report
Continual Match Based Training in Pommerman: Technical Report
Peng Peng
Liang Pang
Yufeng Yuan
Chao Gao
CLL
114
12
0
18 Dec 2018
Using Monte Carlo Tree Search as a Demonstrator within Asynchronous Deep
  RL
Using Monte Carlo Tree Search as a Demonstrator within Asynchronous Deep RL
Bilal Kartal
Pablo Hernandez-Leal
Matthew E. Taylor
OffRL
175
9
0
30 Nov 2018
A Survey and Critique of Multiagent Deep Reinforcement Learning
A Survey and Critique of Multiagent Deep Reinforcement Learning
Pablo Hernandez-Leal
Bilal Kartal
Matthew E. Taylor
OffRL
301
646
0
12 Oct 2018
Backplay: "Man muss immer umkehren"
Backplay: "Man muss immer umkehren"
Cinjon Resnick
R. Raileanu
Sanyam Kapoor
Alex Peysakhovich
Dong Wang
Joan Bruna
OffRL
288
49
0
18 Jul 2018
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