Delayed Deep Deterministic Policy Gradient

Delayed Deep Deterministic Policy Gradient (TD3) is a deep reinforcement learning algorithm designed to address the overestimation bias inherent in actor-critic methods for continuous control tasks. Current research focuses on improving TD3's performance and applicability across diverse domains, including robotics, autonomous driving, database optimization, and financial trading, often incorporating modifications like adaptive bias exploitation or hybrid approaches with other algorithms. These advancements demonstrate TD3's effectiveness in solving complex control problems and its growing importance as a robust and versatile tool for various real-world applications.

Papers

May 24, 2024

TD3 Based Collision Free Motion Planning for Robot Navigation
Hao Liu, Yi Shen, Chang Zhou, Yuelin Zou, Zijun Gao, Qi Wang
Collision Free Robot Navigation Autonomous Navigation System Delayed Deep Deterministic Policy Gradient

May 15, 2024

Chaos-based reinforcement learning with TD3
Toshitaka Matsuki, Yusuke Sakemi, Kazuyuki Aihara
Reinforcement Learning Delayed Deep Deterministic Policy Gradient Intrinsic Exploration

April 8, 2024

IA2: Leveraging Instance-Aware Index Advisor with Reinforcement Learning for Diverse Workloads
Taiyi Wang, Eiko Yoneki
Reinforcement Learning Index Decomposition Learned Index Market Index Delayed Deep Deterministic Policy Gradient Data Workload Temporal Action Abstraction

February 14, 2024

Exploiting Estimation Bias in Deep Double Q-Learning for Actor-Critic Methods
Alberto Sinigaglia, Niccolò Turcato, Alberto Dalla Libera, Ruggero Carli, Gian Antonio Susto
Reinforcement Learning Policy Learning Actor Critic Estimation Bias Double Deep Q Learning Delayed Deep Deterministic Policy Gradient

September 30, 2023

Deep Reinforcement Learning for Autonomous Vehicle Intersection Navigation
Badr Ben Elallid, Hamza El Alaoui, Nabil Benamar
Deep Reinforcement Learning Autonomous Driving Autonomous Vehicle Dense Traffic Delayed Deep Deterministic Policy Gradient

July 31, 2022

Sampling, Communication, and Prediction Co-Design for Synchronizing the Real-World Device and Digital Model in Metaverse
Zhen Meng, Changyang She, Guodong Zhao, Daniele De Martini
Open Sampling 3D Model Co Design Ubiquitous Semantic Metaverse Mixed Reality Delayed Deep Deterministic Policy Gradient Constrained Deep Reinforcement Learning

July 5, 2022

Deep Reinforcement Learning Approach for Trading Automation in The Stock Market
Taylan Kabbani, Ekrem Duman
Deep Reinforcement Learning Markov Decision Process Human Decision Deep Reinforcement Learning Approach Stock Market Delayed Deep Deterministic Policy Gradient Partially Observed Markov Decision Process Automated Cryptocurrency Trading

February 15, 2022

Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Persevering EdgeIoT
Jingjing Zheng, Kai Li, Naram Mhaisen, Wei Ni, Eduardo Tovar, Mohsen Guizani
Federated Learning Long Short Term Memory Deep Reinforcement Online Resource Allocation Delayed Deep Deterministic Policy Gradient

January 14, 2022

Reinforcement Learning based Air Combat Maneuver Generation
Muhammed Murat Ozbek, Emre Koyuncu
Reinforcement Learning Air Combat Unmanned Combat Delayed Deep Deterministic Policy Gradient

December 22, 2021

Newsvendor Model with Deep Reinforcement Learning
Dylan K. Goetting
Deep Reinforcement Learning Delayed Deep Deterministic Policy Gradient Newsvendor Problem Demand Distribution

November 12, 2021

AWD3: Dynamic Reduction of the Estimation Bias
Dogan C. Cicek, Enes Duran, Baturay Saglam, Kagan Kaya, Furkan B. Mutlu, Suleyman S. Kozat
Constructive Reduction Estimation Bias Policy Algorithm Value Based Deep Reinforcement Learning Delayed Deep Deterministic Policy Gradient State Action Value Policy Policy Gradient