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.

181papers

Papers - Page 4

May 2, 2024

LOQA: Learning with Opponent Q-Learning Awareness
Milad Aghajohari, Juan Agustin Duque, Tim Cooijmans, Aaron Courville
Multi Agent Diverse Opponent General Sum Game Social Awareness Reinforcement Learning Algorithm Opponent Modeling

April 11, 2024

Enhancing Policy Gradient with the Polyak Step-Size Adaption
Yunxiang Li, Rui Yuan, Chen Fan, Mark Schmidt, Samuel Horváth, Robert M. Gower, Martin Takáč
Reinforcement Learning Algorithm Polyak Step Size Faster Convergence Reinforcement Learning Policy Gradient

April 4, 2024

AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale
Adam Pardyl, Michał Wronka, Maciej Wołczyk, Kamil Adamczewski, Tomasz Trzciński, Bartosz Zieliński
Visual Exploration Exploration Task Visual Analogue Scale Soft Actor Critic Reinforcement Learning Algorithm

April 2, 2024

Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Samuel Tovey, Christoph Lohrmann, Christian Holm
Reinforcement Learning Reinforcement Learning Algorithm Chemotactic Partial Differential Equation Multi Agent Reinforcement Learning Micro Robot Path Breaking Emergence Three Sphere Swimmer

March 27, 2024

CaT: Constraints as Terminations for Legged Locomotion Reinforcement Learning
Elliot Chane-Sane, Pierre-Alexandre Leziart, Thomas Flayols, Olivier Stasse, Philippe Souères, Nicolas Mansard
Locomotion Policy Constrained Reinforcement LeArning Reinforcement Learning Algorithm Participation Constraint Early Termination Deep Reinforcement Learning Robot Learning

March 25, 2024

Trajectory Planning of Robotic Manipulator in Dynamic Environment Exploiting DRL
Osama Ahmad, Zawar Hussain, Hammad Naeem
Trajectory Planning Dynamic Environment Ga DRL Reinforcement Learning Algorithm Robot Person Degree of Freedom Robot Deep Deterministic Policy Gradient Robotic Manipulator

March 20, 2024

March 13, 2024

Multi-Objective Optimization Using Adaptive Distributed Reinforcement Learning
Jing Tan, Ramin Khalili, Holger Karl
Multi Objective Reinforcement Learning Algorithm Multi Objective Optimization Reinforcement Learning Single Objective Multi Agent Reinforcement Learning

March 11, 2024

\mathbf{(N,K)}-Puzzle: A Cost-Efficient Testbed for Benchmarking Reinforcement Learning Algorithms in Generative Language Model
Yufeng Zhang, Liyu Chen, Boyi Liu, Yingxiang Yang, Qiwen Cui, Yunzhe Tao, Hongxia Yang
Language Model Generative Language Model Reinforcement Learning Algorithm Reinforcement Learning Benchmark K Content Reinforcement Learning Proximal Policy Optimization Test Bed Direct Policy

March 5, 2024

A Zero-Shot Reinforcement Learning Strategy for Autonomous Guidewire Navigation
Valentina Scarponi, Michel Duprez, Florent Nageotte, Stéphane Cotin
Deep Reinforcement Learning Approach Zero Shot Reinforcement Learning Algorithm Guidewire Segmentation Catheter Path Endovascular Navigation

March 4, 2024

DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation
Xueqing Wu, Rui Zheng, Jingzhen Sha, Te-Lin Wu, Hanyu Zhou, Mohan Tang, Kai-Wei Chang, Nanyun Peng, Haoran Huang
MAESTRO Dataset Reinforcement Learning Algorithm Data Annotation Code Generation

February 26, 2024

February 25, 2024

How Can LLM Guide RL? A Value-Based Approach
Shenao Zhang, Sirui Zheng, Shuqi Ke, Zhihan Liu, Wanxin Jin, Jianbo Yuan, Yingxiang Yang, Hongxia Yang, Zhaoran Wang
Reinforcement Learning Value Based Reinforcement Learning Reinforcement Learning Algorithm Large Language Model Value Based

February 22, 2024

February 14, 2024

How does Your RL Agent Explore? An Optimal Transport Analysis of Occupancy Measure Trajectories
Reabetswe M. Nkhumise, Debabrota Basu, Tony J. Prescott, Aditya Gilra
Environment Exploration Uninformed Exploration Policy Space Reinforcement Learning Optimal Transport Reinforcement Learning Algorithm

February 11, 2024

Using Large Language Models to Automate and Expedite Reinforcement Learning with Reward Machine
Shayan Meshkat Alsadat, Jean-Raphael Gaglione, Daniel Neider, Ufuk Topcu, Zhe Xu
Decomposed Automation Correction Closed Loop Domain Knowledge Reinforcement Learning Algorithm Reward Machine Reinforcement Learning

Reinforcement Learning Algorithm

Papers - Page 4

LOQA: Learning with Opponent Q-Learning Awareness

Enhancing Policy Gradient with the Polyak Step-Size Adaption

AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale

Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning

CaT: Constraints as Terminations for Legged Locomotion Reinforcement Learning

Trajectory Planning of Robotic Manipulator in Dynamic Environment Exploiting DRL

Reinforcement Learning for Online Testing of Autonomous Driving Systems: a Replication and Extension Study

POLICEd RL: Learning Closed-Loop Robot Control Policies with Provable Satisfaction of Hard Constraints

Safety-Aware Reinforcement Learning for Electric Vehicle Charging Station Management in Distribution Network

Multi-Objective Optimization Using Adaptive Distributed Reinforcement Learning

\mathbf{(N,K)}-Puzzle: A Cost-Efficient Testbed for Benchmarking Reinforcement Learning Algorithms in Generative Language Model

A Zero-Shot Reinforcement Learning Strategy for Autonomous Guidewire Navigation

DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation

Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test

QF-tuner: Breaking Tradition in Reinforcement Learning

How Can LLM Guide RL? A Value-Based Approach

Reinforcement Learning with Elastic Time Steps

Model-Based Reinforcement Learning Control of Reaction-Diffusion Problems

How does Your RL Agent Explore? An Optimal Transport Analysis of Occupancy Measure Trajectories

Using Large Language Models to Automate and Expedite Reinforcement Learning with Reward Machine