Positive Reinforcement

Positive reinforcement, a core concept in reinforcement learning (RL), aims to optimize agent behavior by rewarding desired actions. Current research focuses on applying RL across diverse fields, utilizing model architectures like Proximal Policy Optimization (PPO), Deep Q-Networks (DQN), and Actor-Critic methods, often integrated with other techniques such as Koopman operators or graph neural networks. This approach is proving valuable in various applications, from optimizing complex systems like space mission planning and cloud load balancing to enhancing safety in autonomous driving and improving the robustness of large language models. The significance lies in its ability to solve challenging problems requiring adaptability and optimization in complex, dynamic environments.

Papers

December 29, 2024

The intrinsic motivation of reinforcement and imitation learning for sequential tasks
Sao Mai Nguyen
Reinforcement Learning Imitation Learning Positive Reinforcement Intrinsic Motivation Cognitive Robotics Sensorimotor Norm Sequential Task

December 26, 2024

A Reinforcement Learning-Based Task Mapping Method to Improve the Reliability of Clustered Manycores
Fatemeh Hossein-Khani, Omid Akbari
Core Stability Positive Reinforcement Functional Programming Mapping Approach

December 18, 2024

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models
Tommy Nguyen, Mehmet Ergezer, Christian Green
Adversarial Attack Neural Radiance Field Full Model Positive Reinforcement Adversarial Noise

December 17, 2024

Active Reinforcement Learning Strategies for Offline Policy Improvement
Ambedkar Dukkipati, Ranga Shaarad Ayyagari, Bodhisattwa Dasgupta, Parag Dutta, Prabhas Reddy Onteru
Positive Reinforcement Sequential Decision Making Task Agent Environment Interaction Offline Policy Evaluation Trajectory Recovery Active Reinforcement Learning

December 16, 2024

MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Bhavya Sukhija, Stelian Coros, Andreas Krause, Pieter Abbeel, Carmelo Sferrazza
Reinforcement Learning Environment Exploration Positive Reinforcement Intrinsic Reward Information Gain Pure Exploration

December 11, 2024

Ask1: Development and Reinforcement Learning-Based Control of a Custom Quadruped Robot
Yuxing Lu, Yufei Xue, Guiyang Xin, Chenkun Qi, Yan Zhuang
External Control Development Activity Quadrupedal Robot Positive Reinforcement Robot Explanation

December 10, 2024

A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
Jacob Adkins, Michael Bowling, Adam White
LeArning Abstract Practical Method Hyperparameter Tuning Related Hyperparameters Positive Reinforcement Hyperparameter Configuration Modern Reinforcement Learning Hyperparameter Importance

December 5, 2024

Demonstration Selection for In-Context Learning via Reinforcement Learning
Xubin Wang, Jianfei Wu, Yichen Yuan, Mingzhe Li, Deyu Cai, Weijia Jia
LeArning Abstract Context Learning Positive Reinforcement Population Diversity Demonstration Selection

December 4, 2024

December 2, 2024

November 24, 2024

Reinforcement learning-enhanced genetic algorithm for wind farm layout optimization
Guodan Dong, Jianhua Qin, Chutian Wu, Chang Xu, Xiaolei Yang
Reinforcement Learning Optimization Purpose Genetic Algorithm Positive Reinforcement Wind Farm

November 7, 2024

A Reinforcement Learning-Based Automatic Video Editing Method Using Pre-trained Vision-Language Model
Panwen Hu, Nan Xiao, Feifei Li, Yongquan Chen, Rui Huang
Vision Language Model Positive Reinforcement Video Editing Scene Level Representation Editing Editing Method

November 4, 2024

Show, Don't Tell: Learning Reward Machines from Demonstrations for Reinforcement Learning-Based Cardiac Pacemaker Synthesis
John Komp, Dananjay Srinivas, Maria Pacheco, Ashutosh Trivedi
Reinforcement Learning Reward Function Noisy Demonstration Positive Reinforcement Design Specification Reward Machine Uncertain Episode Length

October 31, 2024

RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning
Yujie Zhao, Jose Efraim Aguilar Escamill, Weyl Lu, Huazheng Wang
Reinforcement Learning LeArning Abstract Risk Sensitive Positive Reinforcement Preference Based Reinforcement Learning Quantile Temporal Difference Risk Sensitive Algorithm

Positive Reinforcement

Papers

The intrinsic motivation of reinforcement and imitation learning for sequential tasks

A Reinforcement Learning-Based Task Mapping Method to Improve the Reliability of Clustered Manycores

AdvIRL: Reinforcement Learning-Based Adversarial Attacks on 3D NeRF Models

Active Reinforcement Learning Strategies for Offline Policy Improvement

MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Ask1: Development and Reinforcement Learning-Based Control of a Custom Quadruped Robot

A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning

Demonstration Selection for In-Context Learning via Reinforcement Learning

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning

Data Acquisition for Improving Model Fairness using Reinforcement Learning

Explore Reinforced: Equilibrium Approximation with Reinforcement Learning

Task Adaptation of Reinforcement Learning-based NAS Agents through Transfer Learning

RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks

Reinforcement learning-enhanced genetic algorithm for wind farm layout optimization

Robot See, Robot Do: Imitation Reward for Noisy Financial Environments

BAMAX: Backtrack Assisted Multi-Agent Exploration using Reinforcement Learning

RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm

A Reinforcement Learning-Based Automatic Video Editing Method Using Pre-trained Vision-Language Model

Show, Don't Tell: Learning Reward Machines from Demonstrations for Reinforcement Learning-Based Cardiac Pacemaker Synthesis

RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning