Novel Reinforcement Learning

Novel reinforcement learning (RL) research focuses on improving RL algorithms' efficiency, robustness, and applicability to complex real-world problems. Current efforts concentrate on developing new architectures and algorithms, such as those incorporating contrastive learning, multi-critic approaches, and hierarchical structures, to enhance performance in diverse domains including autonomous systems, resource management, and generative modeling. These advancements are significant because they address limitations of existing RL methods, paving the way for more effective solutions in areas like network security, energy systems optimization, and personalized medicine. The field is also actively exploring methods for improving the interpretability and safety of RL agents.

Papers

October 19, 2024

A Novel Reinforcement Learning Model for Post-Incident Malware Investigations
Dipo Dunsin, Mohamed Chahine Ghanem, Karim Ouazzane, Vassil Vassilev
Q Learning Comprehensive Investigation Novel Reinforcement Learning Malware Attack Malware Representation Multi Purpose Malware

September 26, 2024

Autonomous Network Defence using Reinforcement Learning
Myles Foley, Chris Hicks, Kate Highnam, Vasilios Mavroudis
Reinforcement Learning Autonomous Agent Cyber Attack Novel Reinforcement Learning Autonomous Network

August 11, 2024

CURLing the Dream: Contrastive Representations for World Modeling in Reinforcement Learning
Victor Augusto Kich, Jair Augusto Bottega, Raul Steinmetz, Ricardo Bedin Grando, Ayano Yorozu, Akihisa Ohya
Reinforcement Learning Contrastive Learning Visual Reinforcement Learning Novel Reinforcement Learning Contrastive Representation DeepMind Control Suite Dream Report World Modeling

August 1, 2024

Reinforcement Learning applied to Insurance Portfolio Pursuit
Edward James Young, Alistair Rogers, Elliott Tong, James Jordon
Reinforcement Learning Sequential Decision Making Problem Novel Reinforcement Learning Portfolio Selection Prediction Market

July 29, 2024

A Method for Fast Autonomy Transfer in Reinforcement Learning
Dinuka Sahabandu, Bhaskar Ramasubramanian, Michail Alexiou, J. Sukarno Mertoguno, Linda Bushnell, Radha Poovendran
Reinforcement Learning Practical Method Value Function Actor Critic Algorithm Novel Reinforcement Learning Autonomy Transfer

June 30, 2024

Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
Sangwoong Yoon, Himchan Hwang, Dohyun Kwon, Yung-Kyun Noh, Frank C. Park
Diffusion Model Inverse Reinforcement Learning Energy Based Model Novel Reinforcement Learning Entropy Maximization

June 28, 2024

Reinforcement Learning for Efficient Design and Control Co-optimisation of Energy Systems
Marine Cauz, Adrien Bolland, Nicolas Wyrsch, Christophe Ballif
Reinforcement Learning Novel Reinforcement Learning Energy System Renewable Energy Source Efficient Design Co Optimization Control Co Reinforcement Learning Application

June 23, 2024

Position: Benchmarking is Limited in Reinforcement Learning Research
Scott M. Jordan, Adam White, Bruno Castro da Silva, Martha White, Philip S. Thomas
Benchmark Platform Benchmark Study Product Specific Position Information Novel Reinforcement Learning Computational Cost Reinforcement Learning Research Benchmark Environment

June 21, 2024

Learning Autonomous Race Driving with Action Mapping Reinforcement Learning
Yuanda Wang, Xin Yuan, Changyin Sun
Novel Reinforcement Learning Autonomous Race Car Action Mapping

June 2, 2024

Deep Reinforcement Learning for Sim-to-Real Policy Transfer of VTOL-UAVs Offshore Docking Operations
Ali M. Ali, Aryaman Gupta, Hashim A. Hashim
Deep Reinforcement Learning Novel Reinforcement Learning Autonomous Landing Vertical Take Off and Landing Modern Deep Reinforcement Learning

May 22, 2024

Large Language Models (LLMs) Assisted Wireless Network Deployment in Urban Settings
Nurullah Sevim, Mostafa Ibrahim, Sabit Ekin
Large Language Model Language Understanding Urban Environment Wireless Network Novel Reinforcement Learning Deterministic Policy Gradient

May 21, 2024

Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing
Amutheezan Sivagnanam, Ava Pettet, Hunter Lee, Ayan Mukhopadhyay, Abhishek Dubey, Aron Laszka
Multi Agent Reinforcement Learning Novel Reinforcement Learning Emergency Response

May 2, 2024

April 16, 2024

Trajectory Planning Using Reinforcement Learning for Interactive Overtaking Maneuvers in Autonomous Racing Scenarios
Levent Ögretmen, Mo Chen, Phillip Pitschi, Boris Lohmann
Reinforcement Learning Trajectory Planning Autonomous Racing Novel Reinforcement Learning Trajectory Planner Safe Overtaking

April 13, 2024

SmartPathfinder: Pushing the Limits of Heuristic Solutions for Vehicle Routing Problem with Drones Using Reinforcement Learning
Navid Mohammad Imran, Myounggyu Won
Reinforcement Learning Various Fast Moving Drone Specific Heuristic Novel Reinforcement Learning Path Finding Cognitive Heuristic Heuristic Solver

March 25, 2024

Skill Q-Network: Learning Adaptive Skill Ensemble for Mapless Navigation in Unknown Environments
Hyunki Seong, David Hyunchul Shim
Unknown Environment Novel Reinforcement Learning Agile Maneuver Mapless Navigation Navigation Skill Adaptive Skill

March 21, 2024

Heuristic Algorithm-based Action Masking Reinforcement Learning (HAAM-RL) with Ensemble Inference Method
Kyuwon Choi, Cheolkyun Rho, Taeyoun Kim, Daewoo Choi
Reinforcement Learning Markov Decision Process Novel Reinforcement Learning Cognitive Heuristic Action Masking

March 18, 2024

Reinforcement Learning with Token-level Feedback for Controllable Text Generation
Wendi Li, Wei Wei, Kaihe Xu, Wenfeng Xie, Dangyang Chen, Yu Cheng
Large Language Model Reinforcement Learning Text Generation Novel Reinforcement Learning Mode Collapse

March 7, 2024

RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning
Boning Li, Zhixuan Fang, Longbo Huang
Reinforcement Learning Novel Reinforcement Learning Action Abstraction Information Extensive Form Game

Novel Reinforcement Learning

Papers

A Novel Reinforcement Learning Model for Post-Incident Malware Investigations

Autonomous Network Defence using Reinforcement Learning

CURLing the Dream: Contrastive Representations for World Modeling in Reinforcement Learning

Reinforcement Learning applied to Insurance Portfolio Pursuit

A Method for Fast Autonomy Transfer in Reinforcement Learning

Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models

Reinforcement Learning for Efficient Design and Control Co-optimisation of Energy Systems

Position: Benchmarking is Limited in Reinforcement Learning Research

Learning Autonomous Race Driving with Action Mapping Reinforcement Learning

Deep Reinforcement Learning for Sim-to-Real Policy Transfer of VTOL-UAVs Offshore Docking Operations

Large Language Models (LLMs) Assisted Wireless Network Deployment in Urban Settings

Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing

Reinforcement Learning-Guided Semi-Supervised Learning

Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback

Trajectory Planning Using Reinforcement Learning for Interactive Overtaking Maneuvers in Autonomous Racing Scenarios

SmartPathfinder: Pushing the Limits of Heuristic Solutions for Vehicle Routing Problem with Drones Using Reinforcement Learning

Skill Q-Network: Learning Adaptive Skill Ensemble for Mapless Navigation in Unknown Environments

Heuristic Algorithm-based Action Masking Reinforcement Learning (HAAM-RL) with Ensemble Inference Method

Reinforcement Learning with Token-level Feedback for Controllable Text Generation

RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning