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

June 9, 2024

ICU-Sepsis: A Benchmark MDP Built from Real Medical Data
Kartik Choudhary, Dhawal Gupta, Philip S. Thomas
Reinforcement Learning Reinforcement Learning Algorithm Medical Data

June 7, 2024

Reinforcement Learning and Regret Bounds for Admission Control
Lucas Weber, Ana Bušić, Jiamin Zhu
Reinforcement Learning Markov Decision Process Reinforcement Learning Algorithm Regret Bound Low Regret Admission Control Customer Side Queue

June 3, 2024

Deep reinforcement learning for weakly coupled MDP's with continuous actions
Francisco Robledo, Urtzi Ayesta, Konstantin Avrachenkov
Deep Reinforcement Learning Action Space Reinforcement Learning Algorithm Lagrangian Relaxation Efficient Policy Learning Continuous Action

June 2, 2024

Learning-Based Verification of Stochastic Dynamical Systems with Neural Network Policies
Thom Badings, Wietze Koops, Sebastian Junges, Nils Jansen
Reinforcement Learning Algorithm State Space Stochastic Dynamical System Neural Network Policy Reach Avoid

May 28, 2024

Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
Zhiyao Luo, Yangchen Pan, Peter Watkinson, Tingting Zhu
Reinforcement Learning Markov Decision Process Offline Reinforcement Learning Reinforcement Learning Algorithm Dynamic Treatment Regime

May 20, 2024

Highway Graph to Accelerate Reinforcement Learning
Zidu Yin, Zhen Zhang, Dong Gong, Stefano V. Albrecht, Javen Q. Shi
Reinforcement Learning Reinforcement Learning Algorithm Policy Reinforcement Learning Model Based Planning Road Network Graph

May 16, 2024

Combining RL and IL using a dynamic, performance-based modulation over learning signals and its application to local planning
Francisco Leiva, Javier Ruiz-del-Solar
Reinforcement Learning Imitation Learning Mobile Robot Reinforcement Learning Algorithm Behavior Cloning Abnormal Signal Modulation Scheme Local Planning

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

May 7, 2024

SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems
Kailash Gogineni, Sai Santosh Dayapule, Juan Gómez-Luna, Karthikeya Gogineni, Peng Wei, Tian Lan, Mohammad Sadrosadati, Onur Mutlu, Guru Venkataramani
Reinforcement Learning System Description Reinforcement Learning Algorithm Efficient Reinforcement Learning Processing in Memory SWIFT DynGFN Tabular Q Learning

May 2, 2024

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 Policy Gradient Reinforcement Learning Algorithm Faster Convergence Polyak Step Size

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