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11/14/2022
NeurIPS 2022 Competition: Driving SMARTS
Driving SMARTS is a regular competition designed to tackle problems caus...
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09/02/2022
Semi-Centralised Multi-Agent Reinforcement Learning with Policy-Embedded Training
Centralised training (CT) is the basis for many popular multi-agent rein...
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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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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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02/19/2020
Efficient Deep Reinforcement Learning through Policy Transfer
Transfer Learning (TL) has shown great potential to accelerate Reinforce...
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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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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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11/10/2018
Learning Shaping Strategies in Human-in-the-loop Interactive Reinforcement Learning
Providing reinforcement learning agents with informationally rich human ...
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09/12/2018
Bayes-ToMoP: A Fast Detection and Best Response Algorithm Towards Sophisticated Opponents
Multiagent algorithms often aim to accurately predict the behaviors of o...
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03/08/2018