Q Learning

Q-learning is a reinforcement learning algorithm aiming to find optimal actions in an environment by learning a Q-function that estimates the expected cumulative reward for each state-action pair. Current research focuses on improving Q-learning's robustness, efficiency, and applicability to complex scenarios, including multi-agent systems, partially observable environments (POMDPs), and those with corrupted rewards, often employing deep learning architectures like deep Q-networks (DQNs) and modifications such as double Q-learning and prioritized experience replay. These advancements are significant for addressing challenges in various fields, such as robotics, autonomous systems, and network optimization, where efficient and reliable decision-making under uncertainty is crucial.

Papers

November 18, 2024

Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning
Théophile Champion, Marek Grześ, Howard Bowman
Reinforcement Learning Q Learning Model Based Reinforcement Learning Inner Structure Gaussian Mixture Model Gaussian Mixture Perception Model

November 13, 2024

Coverage Analysis for Digital Cousin Selection -- Improving Multi-Environment Q-Learning
Talha Bozkus, Tara Javidi, Urbashi Mitra
Q Learning Higher Coverage Rate Kinship Verification Independent Q Learning

November 12, 2024

November 11, 2024

Enhancing Robot Assistive Behaviour with Reinforcement Learning and Theory of Mind
Antonio Andriella, Giovanni Falcone, Silvia Rossi
Reinforcement Learning Theoretical Understanding Q Learning Human Robot Collaboration Human Mind Social Robot Adaptive Robot

November 8, 2024

Reinforcement Learning for Adaptive Resource Scheduling in Complex System Environments
Pochun Li, Yuyang Xiao, Jinghua Yan, Xuan Li, Xiaoye Wang
Reinforcement Learning Q Learning Resource Allocation Complexity Level Dynamic Scheduling

November 7, 2024

November 1, 2024

Evolutionary Multi-agent Reinforcement Learning in Group Social Dilemmas
Brian Mintz, Feng Fu
Reinforcement Learning Multi Agent Reinforcement Learning Q Learning Evolutionary Game Theory Social Dilemma Public Good Game

October 31, 2024

Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis
Jia Lin Hau, Erick Delage, Esther Derman, Mohammad Ghavamzadeh, Marek Petrik
Markov Decision Process System Performance Q Learning Convergence Analysis Microbial Decomposition Model Free

October 27, 2024

Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model
Jing Zhang, Linjiajie Fang, Kexin Shi, Wenjia Wang, Bing-Yi Jing
Reinforcement Learning Offline Reinforcement Learning Q Learning Consistency Model Q Value

October 23, 2024

Optimizing Load Scheduling in Power Grids Using Reinforcement Learning and Markov Decision Processes
Dongwen Luo
Reinforcement Learning Markov Decision Process Q Learning Power Grid Power System Dynamic Scheduling

October 19, 2024

A Novel Reinforcement Learning Model for Post-Incident Malware Investigations
Dipo Dunsin, Mohamed Chahine Ghanem, Karim Ouazzane, Vassil Vassilev
Q Learning Comprehensive Investigation Novel Reinforcement Learning Malware Attack Malware Representation Multi Purpose Malware

October 18, 2024

Streaming Deep Reinforcement Learning Finally Works
Mohamed Elsayed, Gautham Vasan, A. Rupam Mahmood
Reinforcement Learning Deep Reinforcement Learning Q Learning Batch Reinforcement Learning Stream Learning

October 15, 2024

October 14, 2024

October 10, 2024

Q Learning

Papers

Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning

Coverage Analysis for Digital Cousin Selection -- Improving Multi-Environment Q-Learning

Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learning

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization

Enhancing Robot Assistive Behaviour with Reinforcement Learning and Theory of Mind

Reinforcement Learning for Adaptive Resource Scheduling in Complex System Environments

Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning

Think Smart, Act SMARL! Analyzing Probabilistic Logic Driven Safety in Multi-Agent Reinforcement Learning

Evolutionary Multi-agent Reinforcement Learning in Group Social Dilemmas

Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis

Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model

Optimizing Load Scheduling in Power Grids Using Reinforcement Learning and Markov Decision Processes

A Novel Reinforcement Learning Model for Post-Incident Malware Investigations

Streaming Deep Reinforcement Learning Finally Works

MFC-EQ: Mean-Field Control with Envelope Q-Learning for Moving Decentralized Agents in Formation

Diffusion-Based Offline RL for Improved Decision-Making in Augmented ARC Task

Online Statistical Inference for Time-varying Sample-averaged Q-learning

Online waveform selection for cognitive radar

VerifierQ: Enhancing LLM Test Time Compute with Q-Learning-based Verifiers

Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition