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

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 Analogue Scale Reinforcement Learning Algorithm Soft Actor Critic Visual Exploration Exploration Task

April 2, 2024

Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Samuel Tovey, Christoph Lohrmann, Christian Holm
Reinforcement Learning Multi Agent Reinforcement Learning Reinforcement Learning Algorithm Path Breaking Emergence Micro Robot Chemotactic Partial Differential Equation 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
Deep Reinforcement Learning Reinforcement Learning Algorithm Robot Learning Participation Constraint Locomotion Policy Early Termination Constrained Reinforcement LeArning

March 25, 2024

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

March 20, 2024

March 13, 2024

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

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 Reinforcement Learning Proximal Policy Optimization Reinforcement Learning Algorithm Generative Language Model Reinforcement Learning Benchmark K Content 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
Zero Shot Reinforcement Learning Algorithm Deep Reinforcement Learning Approach 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
Code Generation MAESTRO Dataset Reinforcement Learning Algorithm Data Annotation

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
Large Language Model Reinforcement Learning Reinforcement Learning Algorithm Value Based Reinforcement Learning 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
Reinforcement Learning Optimal Transport Environment Exploration Reinforcement Learning Algorithm Policy Space Uninformed Exploration

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
Reinforcement Learning Domain Knowledge Reinforcement Learning Algorithm Closed Loop Decomposed Automation Correction Reward Machine

February 8, 2024

Real-World Fluid Directed Rigid Body Control via Deep Reinforcement Learning
Mohak Bhardwaj, Thomas Lampe, Michael Neunert, Francesco Romano, Abbas Abdolmaleki, Arunkumar Byravan, Markus Wulfmeier, Martin Riedmiller, Jonas Buchli
Reinforcement Learning Deep Reinforcement Learning Reinforcement Learning Algorithm Model Free Reinforcement Learning Fluid Dynamic Deep RL

February 5, 2024

Assessing the Impact of Distribution Shift on Reinforcement Learning Performance
Ted Fujimoto, Joshua Suetterlein, Samrat Chatterjee, Auroop Ganguly
Reinforcement Learning Global Impact Distribution Shift Reinforcement Learning Algorithm Reinforcement Learning Performance

Reinforcement Learning Algorithm

Papers

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

Q-FOX Learning: 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

Real-World Fluid Directed Rigid Body Control via Deep Reinforcement Learning

Assessing the Impact of Distribution Shift on Reinforcement Learning Performance