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 27, 2023

Replay across Experiments: A Natural Extension of Off-Policy RL
Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen, Tuomas Haarnoja, Sandy Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin Riedmiller, Nicolas Heess, Markus Wulfmeier
Reinforcement Learning Algorithm Optical Experiment Policy Reinforcement Learning RePLAy Loss Natural Extension Data Replay

November 21, 2023

Decentralised Q-Learning for Multi-Agent Markov Decision Processes with a Satisfiability Criterion
Keshav P. Keval, Vivek S. Borkar
Multi Agent Reinforcement Learning Algorithm Decentralized FL Satisfiability Problem Gossip Algorithm Pre Specified Agent Specific Approachability Problem

November 16, 2023

Runtime Verification of Learning Properties for Reinforcement Learning Algorithms
Tommaso Mannucci, Julio de Oliveira Filho
Reinforcement Learning Practical Algorithm Reinforcement Learning Algorithm Runtime Verification

November 14, 2023

Deep Reinforcement Learning for 2D Physics-Based Object Manipulation in Clutter
Luca Renna
Deep Reinforcement Learning Markov Decision Process Policy Gradient 2 Dimensional Reinforcement Learning Algorithm Dense Clutter Modern Reinforcement Learning

November 12, 2023

An advantage based policy transfer algorithm for reinforcement learning with measures of transferability
Md Ferdous Alam, Parinaz Naghizadeh, David Hoelzle
Reinforcement Learning Reinforcement Learning Algorithm Task Transferability Metric Library Advantage Feedback Transfer Reinforcement Learning Policy Transfer

November 6, 2023

Reinforcement Learning for Safety Testing: Lessons from A Mobile Robot Case Study
Tom P. Huck, Martin Kaiser, Constantin Cronrath, Bengt Lennartson, Torsten Kröger, Tamim Asfour
Reinforcement Learning Collision Avoidance Reinforcement Learning Algorithm Critical Lesson Safety Critical Safety Validation

November 3, 2023

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 22, 2023

Learning to bag with a simulation-free reinforcement learning framework for robots
Francisco Munguia-Galeano, Jihong Zhu, Juan David Hernández, Ze Ji
LeArning Abstract Non Humanoid Robot Reinforcement Learning Algorithm Stable Bagging Evolutionary Bagging

October 13, 2023

PAGE: Equilibrate Personalization and Generalization in Federated Learning
Qian Chen, Zilong Wang, Jiaqi Hu, Haonan Yan, Jianying Zhou, Xiaodong Lin
Strong Generalization Reinforcement Learning Algorithm Global Model Local Model Web Page

October 7, 2023

Improving Offline-to-Online Reinforcement Learning with Q Conditioned State Entropy Exploration
Ziqi Zhang, Xiao Xiong, Zifeng Zhuang, Jinxin Liu, Donglin Wang
Reinforcement Learning Offline Reinforcement Learning Reinforcement Learning Algorithm Online Fine Tuning Entropy Exploration

September 18, 2023

Privileged to Predicted: Towards Sensorimotor Reinforcement Learning for Urban Driving
Ege Onat Özsüer, Barış Akgün, Fatma Güney
Reinforcement Learning Autonomous Driving Reinforcement Learning Algorithm Privileged Information Urban Driving Multiple Prediction Privileged Feature Sensorimotor Policy

September 16, 2023

Stylized Table Tennis Robots Skill Learning with Incomplete Human Demonstrations
Xiang Zhu, Zixuan Chen, Jianyu Chen
Reinforcement Learning Reinforcement Learning Algorithm Expert Demonstration Table Tennis Complex Robotic Task

September 7, 2023

Navigation Through Endoluminal Channels Using Q-Learning
Oded Medina, Liora Kleinburd, Nir Shvalb
Q Learning Reinforcement Learning Algorithm Local Navigation

September 1, 2023

End-to-end Lidar-Driven Reinforcement Learning for Autonomous Racing
Meraj Mammadov
Reinforcement Learning Reinforcement Learning Algorithm Reinforcement Learning Agent Autonomous Racing Racing Scenario

August 28, 2023

Target-independent XLA optimization using Reinforcement Learning
Milan Ganai, Haichen Li, Theodore Enns, Yida Wang, Randy Huang
Reinforcement Learning Deep Reinforcement Learning Reinforcement Learning Algorithm Iterative Optimization LLM Based Machine Translation Single Population Optimization Task

July 9, 2023

A User Study on Explainable Online Reinforcement Learning for Adaptive Systems
Andreas Metzger, Jan Laufer, Felix Feit, Klaus Pohl
Deep Reinforcement Learning Reinforcement Learning Algorithm Online Reinforcement Learning User Study Explainable Reinforcement Learning Adaptive System

July 7, 2023

Action-State Dependent Dynamic Model Selection
Francesco Cordoni, Alessio Sancetta
Optimal Policy Reinforcement Learning Algorithm Dynamic Programming Portfolio Selection

June 30, 2023

Design of Induction Machines using Reinforcement Learning
Yasmin SarcheshmehPour, Tommi Ryyppo, Victor Mukherjee, Alex Jung
Reinforcement Learning Product Design Reinforcement Learning Algorithm Induction Motor Electrical Machine