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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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05/18/2022
A2C is a special case of PPO
Advantage Actor-critic (A2C) and Proximal Policy Optimization (PPO) are ...
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03/16/2022
Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed Agents
Multi-agent reinforcement learning is difficult to be applied in practic...
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02/09/2022
Revisiting QMIX: Discriminative Credit Assignment by Gradient Entropy Regularization
In cooperative multi-agent systems, agents jointly take actions and rece...
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06/01/2021
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment
Extending transfer learning to cooperative multi-agent reinforcement lea...
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05/09/2020
Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising
Bipartite b-matching is fundamental in algorithm design, and has been wi...
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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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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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09/25/2019
Independent Generative Adversarial Self-Imitation Learning in Cooperative Multiagent Systems
Many tasks in practice require the collaboration of multiple agents thro...
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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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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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09/10/2018
Learning to Advertise with Adaptive Exposure via Constrained Two-Level Reinforcement Learning
For online advertising in e-commerce, the traditional problem is to assi...
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03/01/2018
