Reinforcement Learning Algorithm

Reinforcement learning (RL) algorithms train agents to make optimal decisions by interacting with an environment and maximizing cumulative rewards. Current research emphasizes improving RL's efficiency and stability, focusing on areas like model-based methods incorporating techniques such as Monte Carlo Tree Search, the development of novel algorithms for specific applications (e.g., traffic control, robotics), and addressing challenges in high-dimensional or partially observable environments. The impact of RL spans diverse fields, from optimizing resource allocation in complex systems to developing more effective personalized interventions in healthcare and improving the efficiency of robotic control systems.

Papers

November 30, 2022

November 28, 2022

Inapplicable Actions Learning for Knowledge Transfer in Reinforcement Learning
Leo Ardon, Alberto Pozanco, Daniel Borrajo, Sumitra Ganesh
Reinforcement Learning Action Space Knowledge Transfer Reinforcement Learning Algorithm Action Model Action Learning

November 20, 2022

Safe Reinforcement Learning using Data-Driven Predictive Control
Mahmoud Selim, Amr Alanwar, M. Watheq El-Kharashi, Hazem M. Abbas, Karl H. Johansson
Reinforcement Learning Data Driven Reinforcement Learning Algorithm Safe Reinforcement Learning Safety Layer

November 8, 2022

Pretraining in Deep Reinforcement Learning: A Survey
Zhihui Xie, Zichuan Lin, Junyou Li, Shuai Li, Deheng Ye
Reinforcement Learning Timely Survey Deep Reinforcement Learning Reinforcement Learning Algorithm

November 6, 2022

October 26, 2022

Quantum deep recurrent reinforcement learning
Samuel Yen-Chi Chen
Reinforcement Learning Deep Reinforcement Learning Quantum Machine Learning Reinforcement Learning Algorithm Quantum Physic Quantum Reinforcement Learning Q$ Learning

October 20, 2022

Task Phasing: Automated Curriculum Learning from Demonstrations
Vaibhav Bajaj, Guni Sharon, Peter Stone
Reinforcement Learning Reinforcement Learning Algorithm Inverse Reinforcement Learning Curriculum Learning Sparse Reward Noisy Demonstration Informative Reward

October 15, 2022

Reinforcement Learning for ConnectX
Sheel Shah, Shubham Gupta
Reinforcement Learning Reinforcement Learning Algorithm Two Player Connection Game

October 11, 2022

Discovered Policy Optimisation
Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schroeder de Witt, Jakob Foerster
Reinforcement Learning Reinforcement Learning Algorithm Policy OpTimization

October 3, 2022

MSRL: Distributed Reinforcement Learning with Dataflow Fragments
Huanzhou Zhu, Bo Zhao, Gang Chen, Weifeng Chen, Yijie Chen, Liang Shi, Yaodong Yang, Peter Pietzuch, Lei Chen
Reinforcement Learning Reinforcement Learning Algorithm Dataflow Architecture

September 29, 2022

Reinforcement Learning Algorithms: An Overview and Classification
Fadi AlMahamid, Katarina Grolinger
Reinforcement Learning Classification Code Autonomous System Reinforcement Learning Algorithm

September 28, 2022

MultiRoboLearn: An open-source Framework for Multi-robot Deep Reinforcement Learning
Junfeng Chen, Fuqin Deng, Yuan Gao, Junjie Hu, Xiyue Guo, Guanqi Liang, Tin Lun Lam
Multi Robot System Reinforcement Learning Algorithm Open Source Framework Real World Multi Robot Multi Robot Application

September 25, 2022

Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation
Vittorio Giammarino, James Queeney, Lucas C. Carstensen, Michael E. Hasselmo, Ioannis Ch. Paschalidis
Reinforcement Learning Technical Challenge Emerging Opportunity Reinforcement Learning Algorithm Local Navigation Sparse Reward 3D Animal

September 21, 2022

LCRL: Certified Policy Synthesis via Logically-Constrained Reinforcement Learning
Hosein Hasanbeig, Daniel Kroening, Alessandro Abate
Markov Decision Process Reinforcement Learning Algorithm Model Free Reinforcement Learning Constrained Reinforcement Learning Policy Synthesis B\"uchi Automaton

August 16, 2022

Making Reinforcement Learning Work on Swimmer
Maël Franceschetti, Coline Lacoux, Ryan Ohouens, Antonin Raffin, Olivier Sigaud
Reinforcement Learning Reinforcement Learning Algorithm Reinforcement Learning Research Model Based Policy

August 2, 2022

Heterogeneous-Agent Mirror Learning: A Continuum of Solutions to Cooperative MARL
Jakub Grudzien Kuba, Xidong Feng, Shiyao Ding, Hao Dong, Jun Wang, Yaodong Yang
Solution Path Reinforcement Learning Algorithm Cooperative Multi Agent Reinforcement Learning Multi Agent MuJoCo Heterogeneous Multi Agent Reinforcement Learning Continuum Tip

July 30, 2022

Solving the vehicle routing problem with deep reinforcement learning
Simone Foa, Corrado Coppola, Giorgio Grani, Laura Palagi
Reinforcement Learning Deep Reinforcement Learning Markov Decision Process Reinforcement Learning Algorithm Vehicle Plan Right Problem NP Hard Combinatorial Optimization Problem

July 26, 2022

Semi-analytical Industrial Cooling System Model for Reinforcement Learning
Yuri Chervonyi, Praneet Dutta, Piotr Trochim, Octavian Voicu, Cosmin Paduraru, Crystal Qian, Emre Karagozler, Jared Quincy Davis, Richard Chippendale, Gautam Bajaj, Sims Witherspoon, Jerry Luo
Reinforcement Learning Reinforcement Learning Algorithm Reinforcement Learning Research Simulation Fidelity Multi Physic Simulation Industrial Cooling System