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Near Optimal Behavior via Approximate State Abstraction

Near Optimal Behavior via Approximate State Abstraction

15 January 2017
David Abel
D Ellis Hershkowitz
Michael L. Littman
    OffRL
ArXiv (abs)PDFHTML

Papers citing "Near Optimal Behavior via Approximate State Abstraction"

50 / 87 papers shown
Title
Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications
Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications
Christoph R. Landolt
Christoph Würsch
Roland Meier
Alain Mermoud
Julian Jang-Jaccard
AAML
10
0
0
26 May 2025
J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization
J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization
Austin Xu
Yilun Zhou
Xuan-Phi Nguyen
Caiming Xiong
Shafiq Joty
ELMLRM
146
0
0
19 May 2025
Octopus: Alleviating Hallucination via Dynamic Contrastive Decoding
Wei Suo
Lijun Zhang
Mengyang Sun
Lin Yuanbo Wu
Peng Wang
Yize Zhang
MLLMVLM
108
3
0
01 Mar 2025
Approximate State Abstraction for Markov Games
Approximate State Abstraction for Markov Games
Hiroki Ishibashi
Kenshi Abe
Atsushi Iwasaki
82
0
0
20 Dec 2024
On shallow planning under partial observability
On shallow planning under partial observability
Randy Lefebvre
Audrey Durand
OffRL
71
1
0
22 Jul 2024
Satisficing Exploration for Deep Reinforcement Learning
Satisficing Exploration for Deep Reinforcement Learning
Dilip Arumugam
Saurabh Kumar
Ramki Gummadi
Benjamin Van Roy
67
1
0
16 Jul 2024
An Optimal Tightness Bound for the Simulation Lemma
An Optimal Tightness Bound for the Simulation Lemma
Sam Lobel
Ronald E. Parr
49
2
0
24 Jun 2024
Learning Abstract World Model for Value-preserving Planning with Options
Learning Abstract World Model for Value-preserving Planning with Options
Rafael Rodríguez-Sánchez
George Konidaris
86
1
0
22 Jun 2024
iQRL -- Implicitly Quantized Representations for Sample-efficient
  Reinforcement Learning
iQRL -- Implicitly Quantized Representations for Sample-efficient Reinforcement Learning
Aidan Scannell
Kalle Kujanpää
Yi Zhao
Mohammadreza Nakhaei
Dieter Büchler
Joni Pajarinen
SSL
147
5
0
04 Jun 2024
Hierarchical Decision Making Based on Structural Information Principles
Hierarchical Decision Making Based on Structural Information Principles
Xianghua Zeng
Hao Peng
Dingli Su
Angsheng Li
75
0
0
15 Apr 2024
Learning Action-based Representations Using Invariance
Learning Action-based Representations Using Invariance
Max Rudolph
Caleb Chuck
Kevin Black
Misha Lvovsky
S. Niekum
Amy Zhang
76
0
0
25 Mar 2024
Learning with Language-Guided State Abstractions
Learning with Language-Guided State Abstractions
Andi Peng
Ilia Sucholutsky
Belinda Z. Li
T. Sumers
Thomas Griffiths
Jacob Andreas
Julie A. Shah
LM&Ro
87
14
0
28 Feb 2024
Model approximation in MDPs with unbounded per-step cost
Model approximation in MDPs with unbounded per-step cost
Berk Bozkurt
Aditya Mahajan
A. Nayyar
Ouyang Yi
25
2
0
13 Feb 2024
Information-Theoretic State Variable Selection for Reinforcement
  Learning
Information-Theoretic State Variable Selection for Reinforcement Learning
Charles Westphal
Stephen Hailes
Mirco Musolesi
78
3
0
21 Jan 2024
Deep Reinforcement Learning for Autonomous Cyber Operations: A Survey
Deep Reinforcement Learning for Autonomous Cyber Operations: A Survey
Gregory Palmer
Chris Parry
Daniel J.B. Harrold
Chris Willis
AI4CE
88
1
0
11 Oct 2023
Accelerating Monte Carlo Tree Search with Probability Tree State
  Abstraction
Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
Yangqing Fu
Mingdong Sun
Buqing Nie
Yue Gao
90
3
0
10 Oct 2023
Reinforcement Learning by Guided Safe Exploration
Reinforcement Learning by Guided Safe Exploration
Qisong Yang
T. D. Simão
N. Jansen
Simon Tindemans
M. Spaan
OffRLOnRL
76
5
0
26 Jul 2023
Achieving Sample and Computational Efficient Reinforcement Learning by
  Action Space Reduction via Grouping
Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
Yining Li
Peizhong Ju
Ness B. Shroff
56
0
0
22 Jun 2023
Simplified Temporal Consistency Reinforcement Learning
Simplified Temporal Consistency Reinforcement Learning
Yi Zhao
Wenshuai Zhao
Rinu Boney
Arno Solin
Joni Pajarinen
OffRL
72
13
0
15 Jun 2023
Policy Gradient Methods in the Presence of Symmetries and State
  Abstractions
Policy Gradient Methods in the Presence of Symmetries and State Abstractions
Prakash Panangaden
S. Rezaei-Shoshtari
Rosie Zhao
David Meger
Doina Precup
74
4
0
09 May 2023
Hierarchical State Abstraction Based on Structural Information
  Principles
Hierarchical State Abstraction Based on Structural Information Principles
Xianghua Zeng
Hao Peng
Angsheng Li
Chunyang Liu
Lifang He
Philip S. Yu
62
20
0
24 Apr 2023
Safe Explicable Planning
Safe Explicable Planning
Akkamahadevi Hanni
Andrew Boateng
Yu Zhang
50
0
0
04 Apr 2023
Embodied Active Learning of Relational State Abstractions for Bilevel
  Planning
Embodied Active Learning of Relational State Abstractions for Bilevel Planning
Amber Li
Tom Silver
70
10
0
08 Mar 2023
Exploiting Multiple Abstractions in Episodic RL via Reward Shaping
Exploiting Multiple Abstractions in Episodic RL via Reward Shaping
R. Cipollone
G. D. Giacomo
Marco Favorito
Luca Iocchi
F. Patrizi
OffRL
78
3
0
28 Feb 2023
Policy-Induced Self-Supervision Improves Representation Finetuning in
  Visual RL
Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL
Sébastien M. R. Arnold
Fei Sha
SSL
46
0
0
12 Feb 2023
Planning to the Information Horizon of BAMDPs via Epistemic State
  Abstraction
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction
Dilip Arumugam
Satinder Singh
97
4
0
30 Oct 2022
Learning Dynamic Abstract Representations for Sample-Efficient
  Reinforcement Learning
Learning Dynamic Abstract Representations for Sample-Efficient Reinforcement Learning
Mehdi Dadvar
Rashmeet Kaur Nayyar
Siddharth Srivastava
47
0
0
04 Oct 2022
Continuous Monte Carlo Graph Search
Continuous Monte Carlo Graph Search
Kalle Kujanpää
Amin Babadi
Yi Zhao
Arno Solin
Alexander Ilin
Joni Pajarinen
LRM
399
2
0
04 Oct 2022
Continuous MDP Homomorphisms and Homomorphic Policy Gradient
Continuous MDP Homomorphisms and Homomorphic Policy Gradient
S. Rezaei-Shoshtari
Rosie Zhao
Prakash Panangaden
David Meger
Doina Precup
97
20
0
15 Sep 2022
An Analysis of Model-Based Reinforcement Learning From Abstracted
  Observations
An Analysis of Model-Based Reinforcement Learning From Abstracted Observations
Rolf A. N. Starre
Marco Loog
E. Congeduti
F. Oliehoek
OffRL
59
1
0
30 Aug 2022
Learning Neuro-Symbolic Skills for Bilevel Planning
Learning Neuro-Symbolic Skills for Bilevel Planning
Tom Silver
Ashay Athalye
J. Tenenbaum
Tomas Lozano-Perez
L. Kaelbling
105
66
0
21 Jun 2022
Deciding What to Model: Value-Equivalent Sampling for Reinforcement
  Learning
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning
Dilip Arumugam
Benjamin Van Roy
OffRL
80
15
0
04 Jun 2022
Predicate Invention for Bilevel Planning
Predicate Invention for Bilevel Planning
Tom Silver
Rohan Chitnis
Nishanth Kumar
Willie McClinton
Tomás Lozano-Pérez
L. Kaelbling
J. Tenenbaum
189
43
0
17 Mar 2022
Optimal Admission Control for Multiclass Queues with Time-Varying
  Arrival Rates via State Abstraction
Optimal Admission Control for Multiclass Queues with Time-Varying Arrival Rates via State Abstraction
Marc Rigter
Danial Dervovic
Parisa Hassanzadeh
Jason Long
Parisa Zehtabi
Daniele Magazzeni
45
5
0
14 Mar 2022
Approximate Policy Iteration with Bisimulation Metrics
Approximate Policy Iteration with Bisimulation Metrics
Mete Kemertas
Allan D. Jepson
87
8
0
06 Feb 2022
Reducing Planning Complexity of General Reinforcement Learning with
  Non-Markovian Abstractions
Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions
Sultan Javed Majeed
Marcus Hutter
OffRL
133
0
0
26 Dec 2021
On the Unreasonable Efficiency of State Space Clustering in
  Personalization Tasks
On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks
Anton Dereventsov
R. Vatsavai
Clayton Webster
78
5
0
24 Dec 2021
Option Transfer and SMDP Abstraction with Successor Features
Option Transfer and SMDP Abstraction with Successor Features
Dongge Han
Sebastian Tschiatschek
30
1
0
18 Oct 2021
Using Human-Guided Causal Knowledge for More Generalized Robot Task
  Planning
Using Human-Guided Causal Knowledge for More Generalized Robot Task Planning
Semir Tatlidil
Yanqi Liu
Emily Sheetz
R. I. Bahar
Steven Sloman Brown University
101
0
0
09 Oct 2021
An Adaptive State Aggregation Algorithm for Markov Decision Processes
An Adaptive State Aggregation Algorithm for Markov Decision Processes
Guanting Chen
Johann D. Gaebler
M. Peng
Chunlin Sun
Yinyu Ye
66
6
0
23 Jul 2021
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn
Sungtae Lee
Jongwook Choi
H. V. Seijen
Mehdi Fatemi
Honglak Lee
321
5
0
13 Jul 2021
Provably Efficient Representation Selection in Low-rank Markov Decision
  Processes: From Online to Offline RL
Provably Efficient Representation Selection in Low-rank Markov Decision Processes: From Online to Offline RL
Weitong Zhang
Jiafan He
Dongruo Zhou
Amy Zhang
Quanquan Gu
OffRL
72
11
0
22 Jun 2021
Which Mutual-Information Representation Learning Objectives are
  Sufficient for Control?
Which Mutual-Information Representation Learning Objectives are Sufficient for Control?
Kate Rakelly
Abhishek Gupta
Carlos Florensa
Sergey Levine
SSL
77
39
0
14 Jun 2021
Learning Markov State Abstractions for Deep Reinforcement Learning
Learning Markov State Abstractions for Deep Reinforcement Learning
Cameron Allen
Neev Parikh
Omer Gottesman
George Konidaris
BDLOffRL
115
39
0
08 Jun 2021
Provable Representation Learning for Imitation with Contrastive Fourier
  Features
Provable Representation Learning for Imitation with Contrastive Fourier Features
Ofir Nachum
Mengjiao Yang
SSLOffRL
107
39
0
26 May 2021
Dynamic neighbourhood optimisation for task allocation using multi-agent
Dynamic neighbourhood optimisation for task allocation using multi-agent
N. Creech
Natalia Criado
S. Miles
112
1
0
16 Feb 2021
Task-oriented Communication Design in Cyber-Physical Systems: A Survey
  on Theory and Applications
Task-oriented Communication Design in Cyber-Physical Systems: A Survey on Theory and Applications
Arsham Mostaani
T. Vu
Shree Krishna Sharma
Van-Dinh Nguyen
Qi Liao
Symeon Chatzinotas
82
17
0
14 Feb 2021
Metrics and continuity in reinforcement learning
Metrics and continuity in reinforcement learning
Charline Le Lan
Marc G. Bellemare
Pablo Samuel Castro
72
35
0
02 Feb 2021
Disentangled Planning and Control in Vision Based Robotics via Reward
  Machines
Disentangled Planning and Control in Vision Based Robotics via Reward Machines
Alberto Camacho
Jacob Varley
Deepali Jain
Atil Iscen
Dmitry Kalashnikov
51
7
0
28 Dec 2020
Exact Reduction of Huge Action Spaces in General Reinforcement Learning
Exact Reduction of Huge Action Spaces in General Reinforcement Learning
Sultan Javed Majeed
Marcus Hutter
OffRL
31
8
0
18 Dec 2020
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