Proximal Policy Optimization

Proximal Policy Optimization (PPO) is a reinforcement learning algorithm used to train agents to make optimal decisions in complex environments, with a current research focus on improving its efficiency and robustness. Recent work explores enhancements such as refined credit assignment methods (e.g., VinePPO), incorporation of human feedback and safety mechanisms (e.g., HI-PPO, PRPO), and addressing challenges in high-dimensional spaces and sample efficiency through techniques like diffusion model integration. These advancements are significant for various applications, including robotics, autonomous systems, and large language model alignment, where PPO's ability to learn effective policies from interactions with the environment is crucial.

Papers

July 2, 2024

Research on Autonomous Robots Navigation based on Reinforcement Learning
Zixiang Wang, Hao Yan, Yining Wang, Zhengjia Xu, Zhuoyue Wang, Zhizhong Wu
Reinforcement Learning Autonomous Navigation Proximal Policy Optimization DH Research Autonomous Robot Navigation

July 1, 2024

A Deep Reinforcement Learning Approach to Battery Management in Dairy Farming via Proximal Policy Optimization
Nawazish Ali, Rachael Shaw, Karl Mason
Q Learning Proximal Policy Optimization Deep Reinforcement Learning Approach Dairy Farming Battery Management

June 26, 2024

Combining Automated Optimisation of Hyperparameters and Reward Shape
Julian Dierkes, Emma Cramer, Holger H. Hoos, Sebastian Trimpe
Deep Reinforcement Learning Reward Function Proximal Policy Optimization Related Hyperparameters Reward Shaping Optimization Process Simultaneous Optimization

June 25, 2024

Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning
Tianfu Wang, Li Shen, Qilin Fan, Tong Xu, Tongliang Liu, Hui Xiong
Proximal Policy Optimization Resource Allocation Virtual Network REinforcement Learning Network Virtualization Admission Control Multi Objective Reward

June 24, 2024

RaCIL: Ray Tracing based Multi-UAV Obstacle Avoidance through Composite Imitation Learning
Harsh Bansal, Vyom Goyal, Bhaskar Joshi, Akhil Gupta, Harikumar Kandath
Imitation Learning Unmanned Aerial Vehicle Collision Avoidance Obstacle Avoidance Proximal Policy Optimization Ray Tracing Generative Adversarial Imitation Learning

June 20, 2024

Learning to Transfer for Evolutionary Multitasking
Sheng-Hao Wu, Yuxiao Huang, Xingyu Wu, Liang Feng, Zhi-Hui Zhan, Kay Chen Tan
LeArning Abstract Proximal Policy Optimization Actor Critic Evolutionary Operator Multi Task Optimization Evolutionary Multitasking

June 17, 2024

June 12, 2024

Optimizing Deep Reinforcement Learning for Adaptive Robotic Arm Control
Jonaid Shianifar, Michael Schukat, Karl Mason
Deep Reinforcement Learning Proximal Policy Optimization Hyperparameter Optimization Tree Structured Parzen Estimator

June 10, 2024

Adaptive Opponent Policy Detection in Multi-Agent MDPs: Real-Time Strategy Switch Identification Using Running Error Estimation
Mohidul Haque Mridul, Mohammad Foysal Khan, Redwan Ahmed Rizvee, Md Mosaddek Khan
Multi Agent Reinforcement Learning Multi Agent Proximal Policy Optimization Trust Region Policy Optimization Opponent Modeling Error Estimation

June 6, 2024

May 28, 2024

PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning
Martin Balla, George E. M. Long, James Goodman, Raluca D. Gaina, Diego Perez-Liebana
Multi Agent Reinforcement Learning Proximal Policy Optimization Reinforcement Learning Agent Multi Agent Setting Game Playing Agent Tabletop Game

May 27, 2024

Linear Function Approximation as a Computationally Efficient Method to Solve Classical Reinforcement Learning Challenges
Hari Srikanth
Reinforcement Learning Proximal Policy Optimization Linear Function Approximation Natural Policy Gradient Efficient Method Trust Region Policy Optimization

May 24, 2024

Human-in-the-loop Reinforcement Learning for Data Quality Monitoring in Particle Physics Experiments
Olivia Jullian Parra, Julián García Pardiñas, Lorenzo Del Pianta Pérez, Maximilian Janisch, Suzanne Klaver, Thomas Lehéricy, Nicola Serra
Proximal Policy Optimization Data Quality High Energy Physic Human in the Loop Reinforcement Particle Physic

May 7, 2024

Proximal Policy Optimization with Adaptive Exploration
Andrei Lixandru
Reinforcement Learning Proximal Policy Optimization Adaptive Exploration

May 6, 2024

Federated Reinforcement Learning with Constraint Heterogeneity
Hao Jin, Liangyu Zhang, Zhihua Zhang
Policy Gradient Proximal Policy Optimization Primal Dual Federated Reinforcement Learning Natural Policy Gradient Heterogeneity Challenge

May 5, 2024

Proximal Policy Optimization

Papers

Research on Autonomous Robots Navigation based on Reinforcement Learning

A Deep Reinforcement Learning Approach to Battery Management in Dairy Farming via Proximal Policy Optimization

Combining Automated Optimisation of Hyperparameters and Reward Shape

Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning

RaCIL: Ray Tracing based Multi-UAV Obstacle Avoidance through Composite Imitation Learning

Learning to Transfer for Evolutionary Multitasking

Is poisoning a real threat to LLM alignment? Maybe more so than you think

P-TA: Using Proximal Policy Optimization to Enhance Tabular Data Augmentation via Large Language Models

SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-Augmented Generation

Optimizing Deep Reinforcement Learning for Adaptive Robotic Arm Control

Adaptive Opponent Policy Detection in Multi-Agent MDPs: Real-Time Strategy Switch Identification Using Running Error Estimation

Transductive Off-policy Proximal Policy Optimization

Reflective Policy Optimization

PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning

Linear Function Approximation as a Computationally Efficient Method to Solve Classical Reinforcement Learning Challenges

Human-in-the-loop Reinforcement Learning for Data Quality Monitoring in Particle Physics Experiments

Proximal Policy Optimization with Adaptive Exploration

Federated Reinforcement Learning with Constraint Heterogeneity

ClothPPO: A Proximal Policy Optimization Enhancing Framework for Robotic Cloth Manipulation with Observation-Aligned Action Spaces

Algorithmic collusion in a two-sided market: A rideshare example