Ling Pan | DeepAI

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448 publications
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Tengyu Ma
97 publications
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Xing Wang
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Lin Zhu
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∙ 07/04/2023

Beyond Conservatism: Diffusion Policies in Offline Multi-agent Reinforcement Learning

We present a novel Diffusion Offline Multi-agent Model (DOM2) for offlin...

0 Zhuoran Li, et al. ∙

∙ 05/26/2023

Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets

Combinatorial optimization (CO) problems are often NP-hard and thus out ...

0 Dinghuai Zhang, et al. ∙

∙ 02/19/2023

Stochastic Generative Flow Networks

Generative Flow Networks (or GFlowNets for short) are a family of probab...

0 Ling Pan, et al. ∙

∙ 02/11/2023

Distributional GFlowNets with Quantile Flows

Generative Flow Networks (GFlowNets) are a new family of probabilistic s...

0 Dinghuai Zhang, et al. ∙

∙ 02/03/2023

Better Training of GFlowNets with Local Credit and Incomplete Trajectories

Generative Flow Networks or GFlowNets are related to Monte-Carlo Markov ...

0 Ling Pan, et al. ∙

∙ 10/07/2022

Generative Augmented Flow Networks

The Generative Flow Network is a probabilistic framework where an agent ...

0 Ling Pan, et al. ∙

∙ 08/30/2022

Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning

Multi-user delay constrained scheduling is important in many real-world ...

2 Pihe Hu, et al. ∙

∙ 05/30/2022

RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch

Training deep reinforcement learning (DRL) models usually requires high ...

0 Yiqin Tan, et al. ∙

∙ 04/19/2022

Network Topology Optimization via Deep Reinforcement Learning

Topology impacts important network performance metrics, including link u...

0 Zhuoran Li, et al. ∙

∙ 11/22/2021

Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification

The idea of conservatism has led to significant progress in offline rein...

0 Ling Pan, et al. ∙

∙ 03/22/2021

Regularized Softmax Deep Multi-Agent Q-Learning

Tackling overestimation in Q-learning is an important problem that has b...

0 Ling Pan, et al. ∙

∙ 10/19/2020

Softmax Deep Double Deterministic Policy Gradients

A widely-used actor-critic reinforcement learning algorithm for continuo...

0 Ling Pan, et al. ∙

∙ 11/11/2019

Multi-Path Policy Optimization

Recent years have witnessed a tremendous improvement of deep reinforceme...

0 Ling Pan, et al. ∙

∙ 09/09/2019

Deterministic Value-Policy Gradients

Reinforcement learning algorithms such as the deep deterministic policy ...

0 Qingpeng Cai, et al. ∙

∙ 03/14/2019

Reinforcement Learning with Dynamic Boltzmann Softmax Updates

Value function estimation is an important task in reinforcement learning...

0 Ling Pan, et al. ∙

∙ 07/10/2018

Generalized deterministic policy gradient algorithms

We study a setting of reinforcement learning, where the state transition...

0 Qingpeng Cai, et al. ∙

∙ 02/13/2018

Rebalancing Dockless Bike Sharing Systems

Bike sharing provides an environment-friendly way for traveling and is b...

0 Ling Pan, et al. ∙

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