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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 801–850 of 1918 papers

TitleStatusHype
An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning—0
A Deep Reinforcement Learning Framework for Contention-Based Spectrum Sharing—0
Channel Estimation via Successive Denoising in MIMO OFDM Systems: A Reinforcement Learning Approach—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
Enhancing reinforcement learning by a finite reward response filter with a case study in intelligent structural control—0
Enhancing Q-Learning with Large Language Model Heuristics—0
Challenging On Car Racing Problem from OpenAI gym—0
An Experimental Comparison Between Temporal Difference and Residual Gradient with Neural Network Approximation—0
Enhancing Classification Performance via Reinforcement Learning for Feature Selection—0
GraMeR: Graph Meta Reinforcement Learning for Multi-Objective Influence Maximization—0
Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning—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
Censored Deep Reinforcement Patrolling with Information Criterion for Monitoring Large Water Resources using Autonomous Surface Vehicles—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
Enhanced Rolling Horizon Evolution Algorithm with Opponent Model Learning: Results for the Fighting Game AI Competition—0
Enhanced Q-Learning Approach to Finite-Time Reachability with Maximum Probability for Probabilistic Boolean Control Networks—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
Cellular traffic offloading via Opportunistic Networking with Reinforcement Learning—0
A new multilayer optical film optimal method based on deep q-learning—0
A Deep Reinforcement Learning Architecture for Multi-stage Optimal Control—0
Action Learning for 3D Point Cloud Based Organ Segmentation—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
Enhanced Deep Q-Learning for 2D Self-Driving Cars: Implementation and Evaluation on a Custom Track Environment—0
Energy Sharing for Multiple Sensor Nodes with Finite Buffers—0
Hidden Markov Model Estimation-Based Q-learning for Partially Observable Markov Decision Process—0
Hierarchical clustering with deep Q-learning—0
Cell Switching in HAPS-Aided Networking: How the Obscurity of Traffic Loads Affects the Decision—0
Hierarchical Deep Q-Learning Based Handover in Wireless Networks with Dual Connectivity—0
Hierarchical Modular Reinforcement Learning Method and Knowledge Acquisition of State-Action Rule for Multi-target Problem—0
Energy Minimization in UAV-Aided Networks: Actor-Critic Learning for Constrained Scheduling Optimization—0
High dimensional precision medicine from patient-derived xenografts—0
High-Dimensional Stock Portfolio Trading with Deep Reinforcement Learning—0
Highway Reinforcement Learning—0
Hippocampal representations emerge when training recurrent neural networks on a memory dependent maze navigation task—0
How to discretize continuous state-action spaces in Q-learning: A symbolic control approach—0
Human and Multi-Agent collaboration in a human-MARL teaming framework—0
Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm—0
Energy-Efficient Power Allocation and Q-Learning-Based Relay Selection for Relay-Aided D2D Communication—0
Hybrid Policies Using Inverse Rewards for Reinforcement Learning—0
Hybrid Q-Learning Applied to Ubiquitous recommender system—0
A new convergent variant of Q-learning with linear function approximation—0
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