Reinforcement Learning Framework

Reinforcement learning (RL) frameworks aim to design agents that learn optimal decision-making strategies through trial-and-error interactions with an environment. Current research emphasizes improving RL's efficiency and applicability across diverse domains, focusing on techniques like actor-critic methods, Proximal Policy Optimization (PPO), and the integration of human feedback for preference tuning. These advancements are driving progress in areas such as robotics, resource management (e.g., power grids, crop management), and solving complex problems in physics and other scientific fields, ultimately leading to more robust and adaptable intelligent systems.

Papers

November 12, 2024

Reinforcement Learning Framework for Quantitative Trading
Alhassan S. Yasin, Prabdeep S. Gill
Reinforcement Learning Financial Market Market Volatility Trading Strategy Reinforcement Learning Framework Aggregate Level Indicator Quantitative Trading

October 19, 2024

Enhancing Robot Navigation Policies with Task-Specific Uncertainty Management
Gokul Puthumanaillam, Paulo Padrao, Jose Fuentes, Leonardo Bobadilla, Melkior Ornik
Uncertainty Map Reinforcement Learning Framework Uncertainty Mitigation

September 27, 2024

TemporalPaD: a reinforcement-learning framework for temporal feature representation and dimension reduction
Xuechen Mu, Zhenyu Huang, Kewei Li, Haotian Zhang, Xiuli Wang, Yusi Fan, Kai Zhang, Fengfeng Zhou
Dimensionality Reduction Deep Learning Framework Dimension Reduction Temporal Representation Reinforcement Learning Framework Temporal Pattern Mining

September 17, 2024

Preference Tuning with Human Feedback on Language, Speech, and Vision Tasks: A Survey
Genta Indra Winata, Hanyang Zhao, Anirban Das, Wenpin Tang, David D. Yao, Shi-Xiong Zhang, Sambit Sahu
Human Language Speech Analysis Human Feedback Vision Task Human Preference Reinforcement Learning Framework Preference Fine Tuning

September 15, 2024

Mitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schema
Waldemar Kołodziejczyk, Mariusz Kaleta
Reinforcement Learning Proximal Policy Optimization Dimension Reduction Heuristic Search Reinforcement Learning Framework Irregular Shape Packing

July 22, 2024

On shallow planning under partial observability
Randy Lefebvre, Audrey Durand
Markov Decision Process Partial Observability Bias Variance Reinforcement Learning Framework Planning Horizon

May 25, 2024

Pausing Policy Learning in Non-stationary Reinforcement Learning
Hyunin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi
Reinforcement Learning Real Time Inference Real World Reinforcement Learning Reinforcement Learning Framework Non Stationary Reinforcement Learning

April 23, 2024

April 19, 2024

MM-PhyRLHF: Reinforcement Learning Framework for Multimodal Physics Question-Answering
Avinash Anand, Janak Kapuriya, Chhavi Kirtani, Apoorv Singh, Jay Saraf, Naman Lal, Jatin Kumar, Adarsh Raj Shivam, Astha Verma, Rajiv Ratn Shah, Roger Zimmermann
Human Feedback Human Like Multimodal Question Multimodal Problem Reinforcement Learning Framework LLM Based Chatbot

September 1, 2023

JoTR: A Joint Transformer and Reinforcement Learning Framework for Dialog Policy Learning
Wai-Chung Kwan, Huimin Wang, Hongru Wang, Zezhong Wang, Xian Wu, Yefeng Zheng, Kam-Fai Wong
Dialogue Model Dialogue Policy Reinforcement Learning Framework Dialog Policy Learning Joint Transformer

August 26, 2023

Reinforcement Learning Based Multi-modal Feature Fusion Network for Novel Class Discovery
Qiang Li, Qiuyang Ma, Weizhi Nie, Anan Liu
Self Supervised Learning Supervised Learning Fusion Network Novel Class Discovery Reinforcement Learning Framework Exploratory Learning Exploration Based Learning

July 21, 2023

Towards Better Fairness-Utility Trade-off: A Comprehensive Measurement-Based Reinforcement Learning Framework
Simiao Zhang, Jitao Bai, Menghong Guan, Yihao Huang, Yueling Zhang, Jun Sun, Geguang Pu
Fairness Notion Reinforcement Learning Framework Fairness Utility Trade Multiple Fairness Metric

June 27, 2023

Learning to Sail Dynamic Networks: The MARLIN Reinforcement Learning Framework for Congestion Control in Tactical Environments
Raffaele Galliera, Mattia Zaccarini, Alessandro Morelli, Roberto Fronteddu, Filippo Poltronieri, Niranjan Suri, Mauro Tortonesi
Reinforcement Learning LeArning Abstract Dynamic Network Congestion Control Reinforcement Learning Framework Tactical Network

March 6, 2023

Sampling-based Exploration for Reinforcement Learning of Dexterous Manipulation
Gagan Khandate, Siqi Shang, Eric T. Chang, Tristan Luca Saidi, Yang Liu, Seth Matthew Dennis, Johnson Adams, Matei Ciocarlie
Reinforcement Learning Model Free Reinforcement Learning Dexterous Manipulation Kinematic Constraint Reinforcement Learning Framework Based Exploration

February 10, 2023

A SWAT-based Reinforcement Learning Framework for Crop Management
Malvern Madondo, Muneeza Azmat, Kelsey Dipietro, Raya Horesh, Michael Jacobs, Arun Bawa, Raghavan Srinivasan, Fearghal O'Donncha
Reinforcement Learning Agricultural Data Decision Making Agent Reinforcement Learning Framework

December 5, 2022

PowRL: A Reinforcement Learning Framework for Robust Management of Power Networks
Anandsingh Chauhan, Mayank Baranwal, Ansuma Basumatary
Reinforcement Learning High Efficiency Power Grid Reinforcement Learning Framework Power Network

May 26, 2022

RACE: A Reinforcement Learning Framework for Improved Adaptive Control of NoC Channel Buffers
Kamil Khan, Sudeep Pasricha, Ryan Gary Kim
Adaptive Control Reinforcement Learning Framework Network on Chip

April 11, 2022

JORLDY: a fully customizable open source framework for reinforcement learning
Kyushik Min, Hyunho Lee, Kwansu Shin, Taehak Lee, Hojoon Lee, Jinwon Choi, Sungho Son
Reinforcement Learning Reinforcement Learning Algorithm Open Source Framework Reinforcement Learning Framework Open Source Reinforcement Learning

February 21, 2022

Reinforcement Learning Framework for Server Placement and Workload Allocation in Multi-Access Edge Computing
Anahita Mazloomi, Hani Sami, Jamal Bentahar, Hadi Otrok, Azzam Mourad
Reinforcement Learning Markov Decision Process Edge Server Reinforcement Learning Framework Workload Aware Multi Access Edge Computing

Reinforcement Learning Framework

Papers

Reinforcement Learning Framework for Quantitative Trading

Enhancing Robot Navigation Policies with Task-Specific Uncertainty Management

TemporalPaD: a reinforcement-learning framework for temporal feature representation and dimension reduction

Preference Tuning with Human Feedback on Language, Speech, and Vision Tasks: A Survey

Mitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schema

On shallow planning under partial observability

Pausing Policy Learning in Non-stationary Reinforcement Learning

MultiSTOP: Solving Functional Equations with Reinforcement Learning

Bi-CL: A Reinforcement Learning Framework for Robots Coordination Through Bi-level Optimization

MM-PhyRLHF: Reinforcement Learning Framework for Multimodal Physics Question-Answering

JoTR: A Joint Transformer and Reinforcement Learning Framework for Dialog Policy Learning

Reinforcement Learning Based Multi-modal Feature Fusion Network for Novel Class Discovery

Towards Better Fairness-Utility Trade-off: A Comprehensive Measurement-Based Reinforcement Learning Framework

Learning to Sail Dynamic Networks: The MARLIN Reinforcement Learning Framework for Congestion Control in Tactical Environments

Sampling-based Exploration for Reinforcement Learning of Dexterous Manipulation

A SWAT-based Reinforcement Learning Framework for Crop Management

PowRL: A Reinforcement Learning Framework for Robust Management of Power Networks

RACE: A Reinforcement Learning Framework for Improved Adaptive Control of NoC Channel Buffers

JORLDY: a fully customizable open source framework for reinforcement learning

Reinforcement Learning Framework for Server Placement and Workload Allocation in Multi-Access Edge Computing