Near Optimal Behavior via Approximate State Abstraction

15 January 2017

Michael L. Littman

Papers citing "Near Optimal Behavior via Approximate State Abstraction"

50 / 87 papers shown

Title
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 Austin Xu Yilun Zhou Xuan-Phi Nguyen Caiming Xiong Shafiq Joty ELM LRM 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 MLLM VLM 108 3 0 01 Mar 2025
Approximate State Abstraction for Markov Games Hiroki Ishibashi Kenshi Abe Atsushi Iwasaki 82 0 0 20 Dec 2024
On shallow planning under partial observability Randy Lefebvre Audrey Durand OffRL 71 1 0 22 Jul 2024
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 Sam Lobel Ronald E. Parr 49 2 0 24 Jun 2024
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 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 Xianghua Zeng Hao Peng Dingli Su Angsheng Li 75 0 0 15 Apr 2024
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 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 Berk Bozkurt Aditya Mahajan A. Nayyar Ouyang Yi 25 2 0 13 Feb 2024
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 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 Yangqing Fu Mingdong Sun Buqing Nie Yue Gao 90 3 0 10 Oct 2023
Reinforcement Learning by Guided Safe Exploration Qisong Yang T. D. Simão N. Jansen Simon Tindemans M. Spaan OffRL OnRL 76 5 0 26 Jul 2023
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 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 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 Xianghua Zeng Hao Peng Angsheng Li Chunyang Liu Lifang He Philip S. Yu 62 20 0 24 Apr 2023
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 Amber Li Tom Silver 70 10 0 08 Mar 2023
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 Sébastien M. R. Arnold Fei Sha SSL 46 0 0 12 Feb 2023
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 Mehdi Dadvar Rashmeet Kaur Nayyar Siddharth Srivastava 47 0 0 04 Oct 2022
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 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 Rolf A. N. Starre Marco Loog E. Congeduti F. Oliehoek OffRL 59 1 0 30 Aug 2022
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 Dilip Arumugam Benjamin Van Roy OffRL 80 15 0 04 Jun 2022
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 Marc Rigter Danial Dervovic Parisa Hassanzadeh Jason Long Parisa Zehtabi Daniele Magazzeni 45 5 0 14 Mar 2022
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 Sultan Javed Majeed Marcus Hutter OffRL 133 0 0 26 Dec 2021
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 Dongge Han Sebastian Tschiatschek 32 1 0 18 Oct 2021
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 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 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 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? Kate Rakelly Abhishek Gupta Carlos Florensa Sergey Levine SSL 77 39 0 14 Jun 2021
Learning Markov State Abstractions for Deep Reinforcement Learning Cameron Allen Neev Parikh Omer Gottesman George Konidaris BDL OffRL 115 39 0 08 Jun 2021
Provable Representation Learning for Imitation with Contrastive Fourier Features Ofir Nachum Mengjiao Yang SSL OffRL 107 39 0 26 May 2021
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 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 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 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 Sultan Javed Majeed Marcus Hutter OffRL 31 8 0 18 Dec 2020