Reinforcement Learning Task

Reinforcement learning (RL) focuses on training agents to make optimal decisions in dynamic environments by maximizing cumulative rewards. Current research emphasizes improving efficiency and robustness through advancements in algorithms like actor-critic methods (with momentum and distributional extensions), and model architectures such as transformers and diffusion models. These improvements address challenges like sample inefficiency, action space explosion in multi-agent settings, and the need for reliable and verifiable RL agents in safety-critical applications, ultimately aiming for more efficient and trustworthy AI systems.

Papers

October 16, 2024

GAN Based Top-Down View Synthesis in Reinforcement Learning Environments
Usama Younus, Vinoj Jayasundara, Shivam Mishra, Suleyman Aslan
Novel View Synthesis Artificial Agent Reinforcement Learning Environment Reinforcement Learning Task

August 13, 2024

Heavy-Ball Momentum Accelerated Actor-Critic With Function Approximation
Yanjie Dong, Haijun Zhang, Gang Wang, Shisheng Cui, Xiping Hu
Markov Decision Process Function Approximation Reinforcement Learning Task Critic Model Heavy Ball Stochastic Policy Gradient

July 18, 2024

PG-Rainbow: Using Distributional Reinforcement Learning in Policy Gradient Methods
WooJae Jeon, KangJun Lee, Jeewoo Lee
Policy Gradient Proximal Policy Optimization Distributional Reinforcement Learning Reinforcement Learning Task Policy Gradient Algorithm

July 5, 2024

Using Petri Nets as an Integrated Constraint Mechanism for Reinforcement Learning Tasks
Timon Sachweh, Pierre Haritz, Thomas Liebig
Reinforcement Learning Trustworthy Artificial Intelligence Reinforcement Learning Task Petri Net Constraint Model Agent State PNPic Model

June 8, 2024

Online Policy Distillation with Decision-Attention
Xinqiang Yu, Chuanguang Yang, Chengqing Yu, Libo Huang, Zhulin An, Yongjun Xu
Reinforcement Learning Task Online Knowledge Distillation Policy Distillation

May 27, 2024

Knowing What Not to Do: Leverage Language Model Insights for Action Space Pruning in Multi-agent Reinforcement Learning
Zhihao Liu, Xianliang Yang, Zichuan Liu, Yifan Xia, Wei Jiang, Yuanyu Zhang, Lijuan Li, Guoliang Fan, Lei Song, Bian Jiang
Language Model Multi Agent Reinforcement Learning Autonomous Agent Active Exploration Reinforcement Learning Task

May 13, 2024

Neural Network Compression for Reinforcement Learning Tasks
Dmitry A. Ivanov, Denis A. Larionov, Oleg V. Maslennikov, Vladimir V. Voevodin
Reinforcement Learning Reinforcement Learning Algorithm Sparsity Increase Efficient Inference Neural Network Compression Neural Network Inference Reinforcement Learning Task

January 27, 2024

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
Chenyu Zhang, Han Wang, Aritra Mitra, James Anderson
Multi Agent Collaboration Federated Reinforcement Learning Finite Time State Action Space Reinforcement Learning Task

December 21, 2023

Diffusion Reward: Learning Rewards via Conditional Video Diffusion
Tao Huang, Guangqi Jiang, Yanjie Ze, Huazhe Xu
Diffusion Model Sparse Reward Reward Report Reinforcement Learning Task Learning Reward

December 20, 2023

In-Context Reinforcement Learning for Variable Action Spaces
Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov
Reinforcement Learning Action Space Contextual Bandit Reinforcement Learning Task

December 6, 2023

SDSRA: A Skill-Driven Skill-Recombination Algorithm for Efficient Policy Learning
Eric H. Jiang, Andrew Lizarraga
Faster Convergence Skill Discovery Reinforcement Learning Task Efficient Policy Learning

November 2, 2023

Diffusion Models for Reinforcement Learning: A Survey
Zhengbang Zhu, Hanye Zhao, Haoran He, Yichao Zhong, Shenyu Zhang, Haoquan Guo, Tingting Chen, Weinan Zhang
Reinforcement Learning Diffusion Model Timely Survey Reinforcement Learning Algorithm Reinforcement Learning Task

October 25, 2023

Finite-Time Analysis of Three-Timescale Constrained Actor-Critic and Constrained Natural Actor-Critic Algorithms
Prashansa Panda, Shalabh Bhatnagar
Actor Critic Constrained Markov Decision Process Finite Time Reinforcement Learning Task

October 23, 2023

Policy Gradient with Kernel Quadrature
Satoshi Hayakawa, Tetsuro Morimura
Gaussian Process Policy Gradient Reinforcement Learning Task Reward Value Kernel Quadrature

October 4, 2023

Neural architecture impact on identifying temporally extended Reinforcement Learning tasks
Victor Vadakechirayath George
Reinforcement Learning Vision Transformer Neural Network Architecture Attention Map Deep Reinforcement Attention Model Reinforcement Learning Task

August 25, 2023

A Game of Bundle Adjustment -- Learning Efficient Convergence
Amir Belder, Refael Vivanti, Ayellet Tal
Localization Focus Bundle Adjustment Reinforcement Learning Task Levenberg Marquardt

June 19, 2023

Practical First-Order Bayesian Optimization Algorithms
Utkarsh Prakash, Aryan Chollera, Kushagra Khatwani, Prabuchandran K. J., Tejas Bodas
Objective Function Practical Application Reinforcement Learning Task First Order Bayesian Optimization

March 7, 2023

Structured State Space Models for In-Context Reinforcement Learning
Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Foerster, Satinder Singh, Feryal Behbahani
Reinforcement Learning State Space Model Long Sequence Reinforcement Learning Task

November 17, 2022

Learning to Communicate with Intent: An Introduction
Miguel Angel Gutierrez-Estevez, Yiqun Wu, Chan Zhou
Reinforcement Learning LeArning Abstract Timely Communication Gentle Introduction Human Intent Reinforcement Learning Task Action Selection Communication System

October 4, 2022

Time-Varying Propensity Score to Bridge the Gap between the Past and Present
Rasool Fakoor, Jonas Mueller, Zachary C. Lipton, Pratik Chaudhari, Alexander J. Smola
Speech Presence Propensity Score Railway BRIDGE Member Reinforcement Learning Task Data Shift