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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 1051–1100 of 1918 papers

TitleStatusHype
A Discrete-Time Switching System Analysis of Q-learning—0
Finite-Time Analysis of Asynchronous Q-learning under Diminishing Step-Size from Control-Theoretic View—0
Final Iteration Convergence Bound of Q-Learning: Switching System Approach—0
Finite-Time Convergence Rates of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning—0
Finite-Time Analysis of Minimax Q-Learning for Two-Player Zero-Sum Markov Games: Switching System Approach—0
Finite-Time Analysis of Simultaneous Double Q-learning—0
Finite-Time Analysis of Whittle Index based Q-Learning for Restless Multi-Armed Bandits with Neural Network Function Approximation—0
Finite-Time Bounds for Two-Time-Scale Stochastic Approximation with Arbitrary Norm Contractions and Markovian Noise—0
Finite-Time Error Analysis of Online Model-Based Q-Learning with a Relaxed Sampling Model—0
Finite-Time Error Analysis of Soft Q-Learning: Switching System Approach—0
FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations—0
Fire Threat Detection From Videos with Q-Rough Sets—0
Fitted Q-Learning for Relational Domains—0
Learning in Discounted-cost and Average-cost Mean-field Games—0
Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning—0
Floyd-Warshall Reinforcement Learning: Learning from Past Experiences to Reach New Goals—0
FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game—0
Forecasting and stabilizing chaotic regimes in two macroeconomic models via artificial intelligence technologies and control methods—0
FPGA Architecture for Deep Learning and its application to Planetary Robotics—0
FRAC-Q-Learning: A Reinforcement Learning with Boredom Avoidance Processes for Social Robots—0
From r to Q^*: Your Language Model is Secretly a Q-Function—0
Frugal Reinforcement-based Active Learning—0
Full Gradient Deep Reinforcement Learning for Average-Reward Criterion—0
Functional Stability of Discounted Markov Decision Processes Using Economic MPC Dissipativity Theory—0
Gap-Dependent Bounds for Federated Q-learning—0
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition—0
Gap-Dependent Bounds for Two-Player Markov Games—0
GenCos' Behaviors Modeling Based on Q Learning Improved by Dichotomy—0
Generative Multi-Agent Q-Learning for Policy Optimization: Decentralized Wireless Networks—0
Genetic Algorithm enhanced by Deep Reinforcement Learning in parent selection mechanism and mutation : Minimizing makespan in permutation flow shop scheduling problems—0
GINO-Q: Learning an Asymptotically Optimal Index Policy for Restless Multi-armed Bandits—0
G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning—0
Goal Reasoning by Selecting Subgoals with Deep Q-Learning—0
Gradient Q(σ, λ): A Unified Algorithm with Function Approximation for Reinforcement Learning—0
GraMeR: Graph Meta Reinforcement Learning for Multi-Objective Influence Maximization—0
Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery—0
Graph Exploration for Effective Multi-agent Q-Learning—0
Graph Neural Network based Agent in Google Research Football—0
Graph Q-Learning for Combinatorial Optimization—0
Greedy-Step Off-Policy Reinforcement Learning—0
Greedy UnMixing for Q-Learning in Multi-Agent Reinforcement Learning—0
Growing Q-Networks: Solving Continuous Control Tasks with Adaptive Control Resolution—0
Guiding Reinforcement Learning Exploration Using Natural Language—0
On Using Hamiltonian Monte Carlo Sampling for Reinforcement Learning Problems in High-dimension—0
Hamilton-Jacobi-Bellman Equations for Q-Learning in Continuous Time—0
Harnessing Deep Q-Learning for Enhanced Statistical Arbitrage in High-Frequency Trading: A Comprehensive Exploration—0
HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning and Monte Carlo Tree Search—0
Hedging of Financial Derivative Contracts via Monte Carlo Tree Search—0
Hedging using reinforcement learning: Contextual k-Armed Bandit versus Q-learning—0
Hidden Incentives for Auto-Induced Distributional Shift—0
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