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02/07/2023
Towards Skilled Population Curriculum for Multi-Agent Reinforcement Learning
Recent advances in multi-agent reinforcement learning (MARL) allow agent...
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01/27/2023
Neural Episodic Control with State Abstraction
Existing Deep Reinforcement Learning (DRL) algorithms suffer from sample...
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10/04/2022
ImmFusion: Robust mmWave-RGB Fusion for 3D Human Body Reconstruction in All Weather Conditions
3D human reconstruction from RGB images achieves decent results in good ...
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10/02/2022
EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model
Unsupervised reinforcement learning (URL) poses a promising paradigm to ...
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09/14/2022
Distributed Multi-Robot Obstacle Avoidance via Logarithmic Map-based Deep Reinforcement Learning
Developing a safe, stable, and efficient obstacle avoidance policy in cr...
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07/25/2022
A Closed-Loop Perception, Decision-Making and Reasoning Mechanism for Human-Like Navigation
Reliable navigation systems have a wide range of applications in robotic...
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07/22/2022
NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction
Implicit neural representations have shown compelling results in offline...
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05/27/2022
Off-Beat Multi-Agent Reinforcement Learning
We investigate model-free multi-agent reinforcement learning (MARL) in e...
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08/16/2021
Neural-to-Tree Policy Distillation with Policy Improvement Criterion
While deep reinforcement learning has achieved promising results in chal...
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06/19/2021
GLIB: Towards Automated Test Oracle for Graphically-Rich Applications
Graphically-rich applications such as games are ubiquitous with attracti...
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12/06/2020
Fever Basketball: A Complex, Flexible, and Asynchronized Sports Game Environment for Multi-agent Reinforcement Learning
The development of deep reinforcement learning (DRL) has benefited from ...
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06/15/2020
Learn to Effectively Explore in Context-Based Meta-RL
Meta reinforcement learning (meta-RL) provides a principled approach for...
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03/10/2020
Exploring Unknown States with Action Balance
Exploration is a key problem in reinforcement learning. Recently bonus-b...
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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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02/10/2020
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
Recently, deep multiagent reinforcement learning (MARL) has become a hig...
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09/06/2019
From Few to More: Large-scale Dynamic Multiagent Curriculum Learning
A lot of efforts have been devoted to investigating how agents can learn...
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09/05/2019
Learning Action-Transferable Policy with Action Embedding
Despite achieving great success on performance in various sequential dec...
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07/26/2019
Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
In multiagent systems (MASs), each agent makes individual decisions but ...
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05/31/2019
Reinforcement Learning Experience Reuse with Policy Residual Representation
Experience reuse is key to sample-efficient reinforcement learning. One ...
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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