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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 1551–1600 of 1918 papers

TitleStatusHype
Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity—0
Agnostic Q-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity—0
A Graph Attention Learning Approach to Antenna Tilt Optimization—0
A Hybrid PAC Reinforcement Learning Algorithm—0
A Hybrid Q-Learning Sine-Cosine-based Strategy for Addressing the Combinatorial Test Suite Minimization Problem—0
A Hysteretic Q-learning Coordination Framework for Emerging Mobility Systems in Smart Cities—0
Adaptive Multi-Agent Deep Reinforcement Learning for Timely Healthcare Interventions—0
AI on the Water: Applying DRL to Autonomous Vessel Navigation—0
A Jointly Optimal Design of Control and Scheduling in Networked Systems under Denial-of-Service Attacks—0
A Large Language Model-Enhanced Q-learning for Capacitated Vehicle Routing Problem with Time Windows—0
A Learning Based Framework for Handling Uncertain Lead Times in Multi-Product Inventory Management—0
Algorithmic Collusion and Price Discrimination: The Over-Usage of Data—0
Algorithmic Collusion in Dynamic Pricing with Deep Reinforcement Learning—0
Algorithmic Collusion under Observed Demand Shocks—0
Algorithmic Trading with Fitted Q Iteration and Heston Model—0
A Lifetime Extended Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles via Self-Learning Fuzzy Reinforcement Learning—0
Almost Sure Convergence Rates and Concentration of Stochastic Approximation and Reinforcement Learning with Markovian Noise—0
A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants—0
A Machine Learning Approach for Prosumer Management in Intraday Electricity Markets—0
A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks—0
A Maintenance Planning Framework using Online and Offline Deep Reinforcement Learning—0
A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret—0
A Modified Q-Learning Algorithm for Rate-Profiling of Polarization Adjusted Convolutional (PAC) Codes—0
Amortized Noisy Channel Neural Machine Translation—0
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways—0
A Multi-step and Resilient Predictive Q-learning Algorithm for IoT with Human Operators in the Loop: A Case Study in Water Supply Networks—0
A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation—0
An Adiabatic Theorem for Policy Tracking with TD-learning—0
Analysis of Multiscale Reinforcement Q-Learning Algorithms for Mean Field Control Games—0
Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent—0
Analysis of Reinforcement Learning Schemes for Trajectory Optimization of an Aerial Radio Unit—0
Analytically Tractable Bayesian Deep Q-Learning—0
Analytics of Business Time Series Using Machine Learning and Bayesian Inference—0
Analyzing Robustness of the Deep Reinforcement Learning Algorithm in Ramp Metering Applications Considering False Data Injection Attack and Defense—0
An Attempt to Model Human Trust with Reinforcement Learning—0
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation—0
An Efficient and Uncertainty-aware Reinforcement Learning Framework for Quality Assurance in Extrusion Additive Manufacturing—0
An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems—0
An Elementary Proof that Q-learning Converges Almost Surely—0
An Empirical Investigation of Value-Based Multi-objective Reinforcement Learning for Stochastic Environments—0
A Nesterov's Accelerated quasi-Newton method for Global Routing using Deep Reinforcement Learning—0
A Network Simulation of OTC Markets with Multiple Agents—0
An Evolutionary Framework for Connect-4 as Test-Bed for Comparison of Advanced Minimax, Q-Learning and MCTS—0
A New Approach for Tactical Decision Making in Lane Changing: Sample Efficient Deep Q Learning with a Safety Feedback Reward—0
A new convergent variant of Q-learning with linear function approximation—0
A new multilayer optical film optimal method based on deep q-learning—0
An Experimental Comparison Between Temporal Difference and Residual Gradient with Neural Network Approximation—0
An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning—0
An Independent Study of Reinforcement Learning and Autonomous Driving—0
An Index Policy Based on Sarsa and Q-learning for Heterogeneous Smart Target Tracking—0
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