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03/02/2023
The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting
Knowing the learning dynamics of policy is significant to unveiling the ...
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10/26/2022
ERL-Re^2: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation
Deep Reinforcement Learning (Deep RL) and Evolutionary Algorithm (EA) ar...
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09/16/2022
Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes
Lying on the heart of intelligent decision-making systems, how policy is...
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04/06/2022
PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations
Deep Reinforcement Learning (DRL) has been a promising solution to many ...
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03/16/2022
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Learning to collaborate is critical in Multi-Agent Reinforcement Learnin...
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12/06/2021
ED2: An Environment Dynamics Decomposition Framework for World Model Construction
Model-based reinforcement learning methods achieve significant sample ef...
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11/19/2021
Uncertainty-aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning
Value estimation is one key problem in Reinforcement Learning. Albeit ma...
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09/14/2021
Exploration in Deep Reinforcement Learning: A Comprehensive Survey
Deep Reinforcement Learning (DRL) and Deep Multi-agent Reinforcement Lea...
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09/12/2021
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation
Discrete-continuous hybrid action space is a natural setting in many pra...
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02/19/2020
Learning When to Transfer among Agents: An Efficient Multiagent Transfer Learning Framework
Transfer Learning has shown great potential to enhance the single-agent ...
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02/18/2020
KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge
Reinforcement learning agents usually learn from scratch, which requires...
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02/10/2020
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
Recently, deep multiagent reinforcement learning (MARL) has become a hig...
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02/10/2020
Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning
In many real-world settings, a team of cooperative agents must learn to ...
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09/30/2019
Efficient meta reinforcement learning via meta goal generation
Meta reinforcement learning (meta-RL) is able to accelerate the acquisit...
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05/27/2019
Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction
Value functions are crucial for model-free Reinforcement Learning (RL) t...
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03/12/2019
Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces
Deep Reinforcement Learning (DRL) has been applied to address a variety ...
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09/25/2018
Hierarchical Deep Multiagent Reinforcement Learning
Despite deep reinforcement learning has recently achieved great successe...
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05/13/2018