Eligibility Traces for Off-Policy Policy Evaluation (original) (raw)

Improving the Efficiency of Off-Policy Reinforcement Learning by Accounting for Past Decisions

Chris Amato

ArXiv, 2021

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META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation

Sitao Luan

2020

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Off-policy learning with recognizers

Anna Koop

Advances in Neural …, 2006

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Efficient Eligibility Traces for Deep Reinforcement Learning

Chris Amato

2018

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Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes

John Loch

1998

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Conditional Importance Sampling for Off-Policy Learning

Anna Harutyunyan

2019

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Stateful Offline Contextual Policy Evaluation and Learning

Angela Zhou

ArXiv, 2021

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Variance-Aware Off-Policy Evaluation with Linear Function Approximation

Yifei Min

2021

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Off-policy learning with options and recognizers

Doina Precup

Advances in Neural …, 2006

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Off-Policy Temporal Difference Learning with Function Approximation

Doina Precup

2001

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On Minimax Optimal Offline Policy Evaluation

Csaba Szepesvari

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Combining Off and On-Policy Training in Model-Based Reinforcement Learning

Arlindo Oliveira

ArXiv, 2021

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Off-Policy Correction for Actor-Critic Methods without Importance Sampling

Furkan Mutlu

arXiv (Cornell University), 2022

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Learning State Features from Policies to Bias Exploration in Reinforcement Learning

M. Afzal Upal

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Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning

Ali Mousavi

ArXiv, 2020

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A convergent O (n) temporal-difference algorithm for off-policy learning with linear function approximation

Richard Sutton

2009

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Model-free Monte Carlo–like policy evaluation

Raphael Fonteneau

Proceedings of the …, 2010

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Policy Learning and Evaluation with Randomized Quasi-Monte Carlo

yi-fan chen

arXiv (Cornell University), 2022

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META-Learning State-based {\lambda} for More Sample-Efficient Policy Evaluation

Sitao Luan

arXiv: Learning, 2019

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Inferring the Optimal Policy using Markov Chain Monte Carlo

Albert Qu

ArXiv, 2019

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Active Offline Policy Selection

Çağlar Gülçehre

arXiv (Cornell University), 2021

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Guided Policy Exploration for Markov Decision Processes Using an Uncertainty-Based Value-of-Information Criterion

Jose Principe

IEEE transactions on neural networks and learning systems, 2018

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An incremental off-policy search in a model-free Markov decision process using a single sample path

Shalabh Bhatnagar

Machine Learning, 2018

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