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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

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Showing 901–950 of 1918 papers

TitleStatusHype
Inverse Policy Evaluation for Value-based Sequential Decision-making—0
A new convergent variant of Q-learning with linear function approximation—0
Energy Consumption and Battery Aging Minimization Using a Q-learning Strategy for a Battery/Ultracapacitor Electric Vehicle—0
Investigating Reinforcement Learning Agents for Continuous State Space Environments—0
Investigating the Edge of Stability Phenomenon in Reinforcement Learning—0
Causal Mean Field Multi-Agent Reinforcement Learning—0
Investigating the Properties of Neural Network Representations in Reinforcement Learning—0
Energy-aware optimization of UAV base stations placement via decentralized multi-agent Q-learning—0
IoT-Aerial Base Station Task Offloading with Risk-Sensitive Reinforcement Learning for Smart Agriculture—0
Energy and Service-priority aware Trajectory Design for UAV-BSs using Double Q-Learning—0
Causal Deep Reinforcement Learning Using Observational Data—0
A New Approach for Tactical Decision Making in Lane Changing: Sample Efficient Deep Q Learning with a Safety Feedback Reward—0
A Deep Reinforcement Learning Approach to Battery Management in Dairy Farming via Proximal Policy Optimization—0
EnCoMP: Enhanced Covert Maneuver Planning with Adaptive Threat-Aware Visibility Estimation using Offline Reinforcement Learning—0
Encoders and Decoders for Quantum Expander Codes Using Machine Learning—0
Is Risk-Sensitive Reinforcement Learning Properly Resolved?—0
"Jam Me If You Can'': Defeating Jammer with Deep Dueling Neural Network Architecture and Ambient Backscattering Augmented Communications—0
Catch Me If You Can: Improving Adversaries in Cyber-Security With Q-Learning Algorithms—0
Empowering Embodied Visual Tracking with Visual Foundation Models and Offline RL—0
Joint Learning of Interactive Spoken Content Retrieval and Trainable User Simulator—0
Joint Learning of Reward Machines and Policies in Environments with Partially Known Semantics—0
Empirical Q-Value Iteration—0
An Evolutionary Framework for Connect-4 as Test-Bed for Comparison of Advanced Minimax, Q-Learning and MCTS—0
KAN v.s. MLP for Offline Reinforcement Learning—0
Empirically Evaluating Multiagent Learning Algorithms—0
Knowledge-Informed Auto-Penetration Testing Based on Reinforcement Learning with Reward Machine—0
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics—0
K-spin Hamiltonian for quantum-resolvable Markov decision processes—0
Language Inference with Multi-head Automata through Reinforcement Learning—0
Large-Scale Traffic Signal Control Using a Novel Multi-Agent Reinforcement Learning—0
Empirical evaluation of a Q-Learning Algorithm for Model-free Autonomous Soaring—0
Late Breaking Results: Breaking Symmetry- Unconventional Placement of Analog Circuits using Multi-Level Multi-Agent Reinforcement Learning—0
Catalytic evolution of cooperation in a population with behavioural bimodality—0
Emergence of cooperation under punishment: A reinforcement learning perspective—0
Emergence of Addictive Behaviors in Reinforcement Learning Agents—0
CARL-DTN: Context Adaptive Reinforcement Learning based Routing Algorithm in Delay Tolerant Network—0
A Network Simulation of OTC Markets with Multiple Agents—0
Learning Automata Based Q-learning for Content Placement in Cooperative Caching—0
A Deep Reinforcement Learning Approach to Efficient Drone Mobility Support—0
Learning-Based Strategy Design for Robot-Assisted Reminiscence Therapy Based on a Developed Model for People with Dementia—0
Learning Best Response Strategies for Agents in Ad Exchanges—0
Learning Control for Air Hockey Striking using Deep Reinforcement Learning—0
Accelerated Structure-Aware Reinforcement Learning for Delay-Sensitive Energy Harvesting Wireless Sensors—0
Learning Dialog Policies from Weak Demonstrations—0
Learning Efficient Parameter Server Synchronization Policies for Distributed SGD—0
Learning Explicit Credit Assignment for Multi-agent Joint Q-learning—0
EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL—0
Learning from Peers: Deep Transfer Reinforcement Learning for Joint Radio and Cache Resource Allocation in 5G RAN Slicing—0
Elastic Decision Transformer—0
Career Path Recommendations for Long-term Income Maximization: A Reinforcement Learning Approach—0
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