Deep Reinforcement Learning Algorithm

Deep reinforcement learning (DRL) algorithms aim to train agents to make optimal decisions in complex environments by learning from experience. Current research focuses on improving sample efficiency, robustness to noise and overfitting, and extending DRL to multi-agent systems and partially observable environments, often employing architectures like recurrent neural networks and adversarial training methods within algorithms such as PPO, A2C, DQN, and TD3. These advancements are crucial for deploying DRL in real-world applications like resource allocation, autonomous driving, and healthcare, where reliable and efficient decision-making is paramount. The development of standardized benchmarks, like ContainerGym, facilitates rigorous comparison and evaluation of different DRL approaches.

Papers

October 21, 2023

One is More: Diverse Perspectives within a Single Network for Efficient DRL
Yiqin Tan, Ling Pan, Longbo Huang
Neural Network Deep Neural Network Deep Reinforcement Learning DRL Algorithm Deep Reinforcement Learning Algorithm Multiple Network Diverse Perspective

August 29, 2023

Adversarial Style Transfer for Robust Policy Optimization in Deep Reinforcement Learning
Md Masudur Rahman, Yexiang Xue
Reinforcement Learning Deep Reinforcement Learning Reinforcement Learning Agent Robust Policy Adversarial Reinforcement Learning Deep Reinforcement Learning Algorithm Adversarial Transfer

July 29, 2023

Dynamic deep-reinforcement-learning algorithm in Partially Observed Markov Decision Processes
Saki Omi, Hyo-Sang Shin, Namhoon Cho, Antonios Tsourdos
Reinforcement Learning Practical Algorithm Markov Decision Process Observable Markov Decision Process Action Sequence Sequential Information Deep Reinforcement Learning Algorithm

July 6, 2023

ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation
Abhijeet Pendyala, Justin Dettmer, Tobias Glasmachers, Asma Atamna
Reinforcement Learning Resource Allocation Reinforcement Learning Benchmark Deep Reinforcement Learning Algorithm

June 22, 2023

Decentralized Multi-Agent Reinforcement Learning with Global State Prediction
Joshua Bloom, Pranjal Paliwal, Apratim Mukherjee, Carlo Pinciroli
Deep Reinforcement Learning Cooperative Transportation State Prediction Agent Training Deep Reinforcement Learning Algorithm

May 10, 2023

Extracting Diagnosis Pathways from Electronic Health Records Using Deep Reinforcement Learning
Lillian Muyama, Antoine Neuraz, Adrien Coulet
Deep Reinforcement Learning Electronic Health Record Real World Dataset Clinical Practice Guideline Deep Reinforcement Learning Algorithm Accurate Diagnosis

April 27, 2023

Adversarial Policy Optimization in Deep Reinforcement Learning
Md Masudur Rahman, Yexiang Xue
Deep Reinforcement Learning Policy OpTimization Based Policy Adversarial Policy PPO Algorithm Deep Reinforcement Learning Algorithm

February 13, 2023

Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning
Bram Grooten, Ghada Sokar, Shibhansh Dohare, Elena Mocanu, Matthew E. Taylor, Mykola Pechenizkiy, Decebal Constantin Mocanu
Reinforcement Learning Deep Reinforcement Learning Noisy Environment Dynamic Sparse Training Task Specific Feature Deep Reinforcement Learning Algorithm

August 8, 2022

Learning-Based Client Selection for Federated Learning Services Over Wireless Networks with Constrained Monetary Budgets
Zhipeng Cheng, Xuwei Fan, Minghui Liwang, Ning Chen, Xianbin Wang
Federated Learning Multi Agent Wireless Network Client Selection Budget Constraint Non Cooperative Game Deep Reinforcement Learning Algorithm

May 18, 2022

A2C is a special case of PPO
Shengyi Huang, Anssi Kanervisto, Antonin Raffin, Weixun Wang, Santiago Ontañón, Rousslan Fernand Julien Dossa
Proximal Policy Optimization Policy Optimization Game AI Deep Reinforcement Learning Algorithm Advantage Actor Critic Special Case Pseudo Code Apical 2 Chamber

April 20, 2022

Comparing Deep Reinforcement Learning Algorithms in Two-Echelon Supply Chains
Francesco Stranieri, Fabio Stella
Deep Reinforcement Learning Algorithm Echelon Supply Chain

March 20, 2022

Reinforcement learning reward function in unmanned aerial vehicle control tasks
Mikhail S. Tovarnov, Nikita V. Bykov
Deep Reinforcement Learning Reward Function Positive Reinforcement Drone Control Deep Reinforcement Learning Algorithm

January 19, 2022

Reinforcement Learning Textbook
Sergey Ivanov
Practical Algorithm Robotics Domain Game AI Proof Pile 2 Deep Reinforcement Learning Algorithm

December 22, 2021

Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment
Aizaz Sharif, Dusica Marijan
Deep Reinforcement Learning Autonomous Driving Native Robustness Autonomous Vehicle Autonomous Framework Deep Reinforcement Learning Algorithm Autonomous Driving Policy

December 10, 2021

Faster Deep Reinforcement Learning with Slower Online Network
Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola
Deep Reinforcement Learning DQN Agent Deep Reinforcement Learning Algorithm Slow Motion Enhanced Network