Approximate information state for approximate planning and reinforcement
learning in partially observed systems

Approximate information state for approximate planning and reinforcement learning in partially observed systems

17 October 2020

Jayakumar Subramanian

Papers citing "Approximate information state for approximate planning and reinforcement learning in partially observed systems"

14 / 14 papers shown

Title
Learning Symbolic Persistent Macro-Actions for POMDP Solving Over Time Celeste Veronese Daniele Meli Alessandro Farinelli 32 0 0 06 May 2025
Dual Filter: A Mathematical Framework for Inference using Transformer-like Architectures Heng-Sheng Chang P. Mehta 39 0 0 01 May 2025
Q-function Decomposition with Intervention Semantics with Factored Action Spaces Junkyu Lee Tian Gao Elliot Nelson Miao Liu D. Bhattacharjya Songtao Lu OffRL 45 0 0 30 Apr 2025
Anticipating Oblivious Opponents in Stochastic Games Shadi Tasdighi Kalat Sriram Sankaranarayanan Ashutosh Trivedi 16 0 0 18 Sep 2024
Bridging State and History Representations: Understanding Self-Predictive RL Tianwei Ni Benjamin Eysenbach Erfan Seyedsalehi Michel Ma Clement Gehring Aditya Mahajan Pierre-Luc Bacon AI4TS AI4CE 22 20 0 17 Jan 2024
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability Chuning Zhu Max Simchowitz Siri Gadipudi Abhishek Gupta 43 13 0 31 Aug 2023
Worst-Case Control and Learning Using Partial Observations Over an Infinite Time-Horizon Aditya Dave Ioannis Faros N. Venkatesh Andreas A. Malikopoulos 23 7 0 28 Mar 2023
Approximate Information States for Worst-Case Control and Learning in Uncertain Systems Aditya Dave N. Venkatesh Andreas A. Malikopoulos 35 7 0 12 Jan 2023
On learning history based policies for controlling Markov decision processes Gandharv Patil Aditya Mahajan Doina Precup OffRL 21 5 0 06 Nov 2022
Reinforcement Learning in Non-Markovian Environments Siddharth Chandak Pratik Shah Vivek Borkar Parth Dodhia OOD 22 7 0 03 Nov 2022
Common Information based Approximate State Representations in Multi-Agent Reinforcement Learning Shitao Xiao V. Subramanian 29 9 0 25 Oct 2021
Robustness and sample complexity of model-based MARL for general-sum Markov games Jayakumar Subramanian Amit Sinha Aditya Mahajan 27 8 0 05 Oct 2021
Online Learning for Unknown Partially Observable MDPs Mehdi Jafarnia-Jahromi Rahul Jain A. Nayyar 31 20 0 25 Feb 2021
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning Wenhao Li Bo Jin Xiangfeng Wang Junchi Yan H. Zha 25 21 0 17 Apr 2020