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1701.04113
Cited By
Near Optimal Behavior via Approximate State Abstraction
15 January 2017
David Abel
D Ellis Hershkowitz
Michael L. Littman
OffRL
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Papers citing
"Near Optimal Behavior via Approximate State Abstraction"
50 / 87 papers shown
Title
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Approximate State Abstraction for Markov Games
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Satisficing Exploration for Deep Reinforcement Learning
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An Optimal Tightness Bound for the Simulation Lemma
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Learning Abstract World Model for Value-preserving Planning with Options
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Mohammadreza Nakhaei
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04 Jun 2024
Hierarchical Decision Making Based on Structural Information Principles
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Learning Action-based Representations Using Invariance
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Misha Lvovsky
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Learning with Language-Guided State Abstractions
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Ilia Sucholutsky
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Jacob Andreas
Julie A. Shah
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Deep Reinforcement Learning for Autonomous Cyber Operations: A Survey
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Chris Parry
Daniel J.B. Harrold
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Yue Gao
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Reinforcement Learning by Guided Safe Exploration
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T. D. Simão
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0
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Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
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Peizhong Ju
Ness B. Shroff
56
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Simplified Temporal Consistency Reinforcement Learning
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Rinu Boney
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Joni Pajarinen
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72
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Policy Gradient Methods in the Presence of Symmetries and State Abstractions
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Rosie Zhao
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74
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Hierarchical State Abstraction Based on Structural Information Principles
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Hao Peng
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Chunyang Liu
Lifang He
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62
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Safe Explicable Planning
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Andrew Boateng
Yu Zhang
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Embodied Active Learning of Relational State Abstractions for Bilevel Planning
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Learning Dynamic Abstract Representations for Sample-Efficient Reinforcement Learning
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Continuous Monte Carlo Graph Search
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Amin Babadi
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Alexander Ilin
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Continuous MDP Homomorphisms and Homomorphic Policy Gradient
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Learning Neuro-Symbolic Skills for Bilevel Planning
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J. Tenenbaum
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105
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Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning
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Predicate Invention for Bilevel Planning
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Rohan Chitnis
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Willie McClinton
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189
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17 Mar 2022
Optimal Admission Control for Multiclass Queues with Time-Varying Arrival Rates via State Abstraction
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Danial Dervovic
Parisa Hassanzadeh
Jason Long
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45
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Approximate Policy Iteration with Bisimulation Metrics
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Marcus Hutter
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On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks
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R. Vatsavai
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Option Transfer and SMDP Abstraction with Successor Features
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R. I. Bahar
Steven Sloman Brown University
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Chunlin Sun
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Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
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Sungtae Lee
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Provably Efficient Representation Selection in Low-rank Markov Decision Processes: From Online to Offline RL
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Learning Markov State Abstractions for Deep Reinforcement Learning
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Metrics and continuity in reinforcement learning
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Deepali Jain
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