Cover Image

Analysis of Off-Policy Multi-Step TD-Learning with Linear Function Approximation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Lee, Donghwan
Format:	Preprint
Published:	2024
Subjects:	Systems and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Analysis of Off-Policy $n$-Step TD-Learning with Linear Function Approximation
by: Lim, Han-Dong, et al.
Published: (2025)

A Simple Finite-Time Analysis of TD Learning with Linear Function Approximation
by: Mitra, Aritra
Published: (2024)

A Concentration Bound for TD(0) with Function Approximation
by: Chandak, Siddharth, et al.
Published: (2023)

Finite-Time Analysis of Simultaneous Double Q-learning
by: Na, Hyunjun, et al.
Published: (2024)

Finite-Time Analysis of Q-Value Iteration for General-Sum Stackelberg Games
by: Jeong, Narim, et al.
Published: (2026)

Lyapunov-Certified Direct Switching Theory for Q-Learning
by: Lee, Donghwan
Published: (2026)

Finite-Time Accuracy of Temporal-Difference Learning Under Schur-Stable Recursions
by: Lee, Donghwan, et al.
Published: (2022)

A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections or Strong Convexity
by: Lee, Wei-Cheng, et al.
Published: (2025)

Deep Q-Learning with Gradient Target Tracking
by: Park, Bum Geun, et al.
Published: (2025)

A primal-dual perspective for distributed TD-learning
by: Lim, Han-Dong, et al.
Published: (2023)

Bellman Residual Minimization for Control: Geometry, Stationarity, and Convergence
by: Lee, Donghwan, et al.
Published: (2026)

Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control
by: Lee, Bruce D., et al.
Published: (2024)

Off Policy Lyapunov Stability in Reinforcement Learning
by: Gill, Sarvan, et al.
Published: (2025)

Approximate Linear Programming for Decentralized Policy Iteration in Cooperative Multi-agent Markov Decision Processes
by: Mandal, Lakshmi, et al.
Published: (2023)

Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits
by: Maity, Sreejeet, et al.
Published: (2025)

SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
by: Mangold, Paul, et al.
Published: (2024)

Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
by: Srikant, R.
Published: (2024)

Approximate Thompson Sampling for Learning Linear Quadratic Regulators with $O(\sqrt{T})$ Regret
by: Kim, Yeoneung, et al.
Published: (2024)

Regret Analysis of Policy Optimization over Submanifolds for Linearly Constrained Online LQG
by: Chang, Ting-Jui, et al.
Published: (2024)

Optimization Solution Functions as Deterministic Policies for Offline Reinforcement Learning
by: Khattar, Vanshaj, et al.
Published: (2024)

Model-Agnostic Zeroth-Order Policy Optimization for Meta-Learning of Ergodic Linear Quadratic Regulators
by: Pan, Yunian, et al.
Published: (2024)

Nonasymptotic Regret Analysis of Adaptive Linear Quadratic Control with Model Misspecification
by: Lee, Bruce D., et al.
Published: (2023)

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
by: Zhang, Chenyu, et al.
Published: (2024)

On Policy Stochasticity in Mutual Information Optimal Control of Linear Systems
by: Enami, Shoju, et al.
Published: (2025)

Conformal Off-Policy Evaluation in Markov Decision Processes
by: Foffano, Daniele, et al.
Published: (2023)

Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way
by: Kwon, Jeongyeol, et al.
Published: (2024)

Beyond the Bellman Fixed Point: Geometry and Fast Policy Identification in Value Iteration
by: Lee, Donghwan
Published: (2026)

Finite Sample Analysis of Tensor Decomposition for Learning Mixtures of Linear Systems
by: Rui, Maryann, et al.
Published: (2024)

A Short Information-Theoretic Analysis of Linear Auto-Regressive Learning
by: Ziemann, Ingvar
Published: (2024)

Harnessing Membership Function Dynamics for Stability Analysis of T-S Fuzzy Systems
by: Lee, Donghwan, et al.
Published: (2024)

Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise
by: Haque, Shaan Ul, et al.
Published: (2023)

A Model-Based Approach to Imitation Learning through Multi-Step Predictions
by: Balim, Haldun, et al.
Published: (2025)

Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
by: Long, Kehan, et al.
Published: (2025)

A Switching System Theory of Q-Learning with Linear Function Approximation
by: Lee, Donghwan, et al.
Published: (2026)

$O(1/k)$ Finite-Time Bound for Non-Linear Two-Time-Scale Stochastic Approximation
by: Chandak, Siddharth
Published: (2025)

Parameter Stress Analysis in Reinforcement Learning: Applying Synaptic Filtering to Policy Networks
by: Abdeen, Zain ul, et al.
Published: (2025)

Mixed Monotonicity Reachability Analysis of Neural ODE: A Trade-Off Between Tightness and Efficiency
by: Sayed, Abdelrahman Sayed, et al.
Published: (2025)

Fitted Q-Iteration via Max-Plus-Linear Approximation
by: Liu, Y., et al.
Published: (2024)

Learning to Sparsify Stochastic Linear Bandits
by: Wang, Zhengmiao, et al.
Published: (2026)

Function Approximation for Reinforcement Learning Controller for Energy from Spread Waves
by: Sarkar, Soumyendu, et al.
Published: (2024)