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Q-Learning

The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances.

( Image credit: Playing Atari with Deep Reinforcement Learning )

Papers

Showing 12011250 of 1918 papers

TitleStatusHype
Deep Q Learning from Dynamic Demonstration with Behavioral Cloning0
Deep Q-Learning with Low Switching Cost0
Double Q-learning: New Analysis and Sharper Finite-time Bound0
Learning Movement Strategies for Moving Target Defense0
Addressing Distribution Shift in Online Reinforcement Learning with Offline Datasets0
Deep Reinforcement Learning-based Anti-jamming Power Allocation in a Two-cell NOMA Network0
Optimistic Exploration with Backward Bootstrapped Bonus for Deep Reinforcement Learning0
Uncertainty Weighted Offline Reinforcement Learning0
Weighted Bellman Backups for Improved Signal-to-Noise in Q-Updates0
Blackwell Online Learning for Markov Decision Processes0
Disentangled Planning and Control in Vision Based Robotics via Reward Machines0
POPO: Pessimistic Offline Policy OptimizationCode0
Assured RL: Reinforcement Learning with Almost Sure Constraints0
Goal Reasoning by Selecting Subgoals with Deep Q-Learning0
Distributed Q-Learning with State Tracking for Multi-agent Networked Control0
Stabilizing Q Learning Via Soft Mellowmax Operator0
Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FELCode0
Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation0
Virtual Autonomous Driving with Reinforcement Learning0
Deploying Reinforcement Learning in Water Transport0
Semi-Supervised Off Policy Reinforcement Learning0
Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation0
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways0
Self-correcting Q-Learning0
Hippocampal representations emerge when training recurrent neural networks on a memory dependent maze navigation task0
A new convergent variant of Q-learning with linear function approximation0
Agnostic Q-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity0
Robust Multi-Agent Reinforcement Learning with Model Uncertainty0
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory0
A Unified Switching System Perspective and Convergence Analysis of Q-Learning Algorithms0
Deep reinforcement learning with a particle dynamics environment applied to emergency evacuation of a room with obstacles0
Real-time Active Vision for a Humanoid Soccer Robot Using Deep Reinforcement Learning0
Reinforcement Learning-based Joint Path and Energy Optimization of Cellular-Connected Unmanned Aerial Vehicles0
Diluted Near-Optimal Expert Demonstrations for Guiding Dialogue Stochastic Policy Optimisation0
Learning Principle of Least Action with Reinforcement LearningCode0
Solving The Lunar Lander Problem under Uncertainty using Reinforcement LearningCode0
Multi-Agent Reinforcement Learning for Markov Routing Games: A New Modeling Paradigm For Dynamic Traffic Assignment0
Provable Multi-Objective Reinforcement Learning with Generative Models0
C-Learning: Learning to Achieve Goals via Recursive Classification0
Constrained Model-Free Reinforcement Learning for Process Optimization0
A deep Q-Learning based Path Planning and Navigation System for Firefighting Environments0
On Using Hamiltonian Monte Carlo Sampling for Reinforcement Learning Problems in High-dimension0
Multi-Agent Reinforcement Learning for Channel Assignment and Power Allocation in Platoon-Based C-V2X Systems0
Reinforced Deep Markov Models With Applications in Automatic Trading0
Reinforcement Learning for Assignment problem0
A Hysteretic Q-learning Coordination Framework for Emerging Mobility Systems in Smart Cities0
Control with adaptive Q-learningCode0
Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment SettingsCode0
Finite-Time Convergence Rates of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning0
DeepFoldit -- A Deep Reinforcement Learning Neural Network Folding Proteins0
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