https://github.com/cheryyunl/paper-list-of-marl
A new paper list for multi-agent reinforcement learning (actively maintained)
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (4.8%) to scientific vocabulary
Repository
A new paper list for multi-agent reinforcement learning (actively maintained)
Basic Info
- Host: GitHub
- Owner: cheryyunl
- Default Branch: master
- Size: 6.84 KB
Statistics
- Stars: 24
- Watchers: 5
- Forks: 2
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Paper-List-of-MARL
A new paper list for multi-agent reinforcement learning (actively maintained), collecting papers since 2018.
Reference: https://github.com/LantaoYu/MARL-Papers
To-do: sub-track summary
Communication
- Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control
- Graph Convolutional Reinforcement Learning
- Biases for Emergent Communication in Multi-agent Reinforcement Learning
- TarMAC: Targeted Multi-Agent Communication
- Learning to Schedule Communication in Multi-agent Reinforcement Learning
- Biases for Emergent Communication in Multi-agent Reinforcement Learning
- Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
Modelling Other Agents
ICLR 2020
Oral
Spotlight
- Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning
- Influence-Based Multi-Agent Exploration
Poster
- Multi-agent Reinforcement Learning for Networked System Control
- CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning
- Multi-Agent Interactions Modeling with Correlated Policies
- Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
- Learning attentional communication for multi-agent cooperation
- Graph Convolutional Reinforcement Learning
NIPS 2019
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents
Biases for Emergent Communication in Multi-agent Reinforcement Learning
ICLR 2019
Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
Learning to Schedule Communication in Multi-agent Reinforcement Learning
M^3RL: Mind-aware Multi-agent Management Reinforcement Learning
Stochastic Prediction of Multi-Agent Interactions from Partial Observations
Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
ICML 2019
- Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning
Actor-Attention-Critic for Multi-Agent Reinforcement Learning
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
NIPS 2018
- Learning others’ intentional models in multi-agent settings using interactive POMDPs
- Inequity aversion improves cooperation in intertemporal social dilemmas
- Learning attentional communication for multi-agent cooperation
- Actor-critic policy optimization in partially observable multiagent environments
- Credit assignment for collective multiagent RL with global rewards
- Multi-agent generative adversarial imitation learning
- Multi-agent reinforcement learning via double averaging primal-dual optimization
- A deep Bayesian policy reuse approach against non-stationary agents
- Multi-agent online learning with asynchronous feedback loss
ICML 2018
- Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations
- Learning to Act inDecentralized Partially Observable MDPs
- Learning Policy Representations in Multiagent Systems
- Mean Field Multi-Agent Reinforcement Learning
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
ICLR 2018
Owner
- Name: Cheryl Liang
- Login: cheryyunl
- Kind: user
- Location: Toronto
- Website: https://cheryyunl.github.io/
- Repositories: 1
- Profile: https://github.com/cheryyunl
Reinforcement Learning, Interactive Learning System
GitHub Events
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- Fork event: 1
Last Year
- Fork event: 1