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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 326350 of 1918 papers

TitleStatusHype
Continuous-time Risk-sensitive Reinforcement Learning via Quadratic Variation Penalty0
From r to Q^*: Your Language Model is Secretly a Q-Function0
Empowering Embodied Visual Tracking with Visual Foundation Models and Offline RL0
Advancing Forest Fire Prevention: Deep Reinforcement Learning for Effective Firebreak Placement0
Traffic Signal Control and Speed Offset Coordination Using Q-Learning for Arterial Road Networks0
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA0
Deep Reinforcement Learning Control for Disturbance Rejection in a Nonlinear Dynamic System with Parametric Uncertainty0
Growing Q-Networks: Solving Continuous Control Tasks with Adaptive Control Resolution0
Superior Genetic Algorithms for the Target Set Selection Problem Based on Power-Law Parameter Choices and Simple Greedy HeuristicsCode0
Laser Learning Environment: A new environment for coordination-critical multi-agent tasksCode1
Data-Driven Knowledge Transfer in Batch Q^* Learning0
Utilizing Maximum Mean Discrepancy Barycenter for Propagating the Uncertainty of Value Functions in Reinforcement Learning0
EnCoMP: Enhanced Covert Maneuver Planning with Adaptive Threat-Aware Visibility Estimation using Offline Reinforcement Learning0
From Two-Dimensional to Three-Dimensional Environment with Q-Learning: Modeling Autonomous Navigation with Reinforcement Learning and no LibrariesCode0
Compressed Federated Reinforcement Learning with a Generative ModelCode0
Semantic-Aware Remote Estimation of Multiple Markov Sources Under Constraints0
DASA: Delay-Adaptive Multi-Agent Stochastic Approximation0
A Fairness-Oriented Reinforcement Learning Approach for the Operation and Control of Shared Micromobility ServicesCode0
Reinforcement Learning for Online Testing of Autonomous Driving Systems: a Replication and Extension Study0
State-Separated SARSA: A Practical Sequential Decision-Making Algorithm with Recovering Rewards0
Neural-Kernel Conditional Mean Embeddings0
A Reinforcement Learning Approach to Dairy Farm Battery Management using Q Learning0
Model-free Resilient Controller Design based on Incentive Feedback Stackelberg Game and Q-learning0
Strategizing against Q-learners: A Control-theoretical Approach0
Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services0
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