Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning

18 July 2023

Papers citing "Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning"

8 / 8 papers shown

Title
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning Caleb Chuck Fan Feng Carl Qi Chang Shi Siddhant Agarwal Amy Zhang S. Niekum 33 0 0 06 May 2025
Object-Centric World Model for Language-Guided Manipulation Youngjoon Jeong Junha Chun S. Cha Taesup Kim OCL VGen 84 0 0 08 Mar 2025
BlendRL: A Framework for Merging Symbolic and Neural Policy Learning Hikaru Shindo Quentin Delfosse D. Dhami Kristian Kersting 33 3 0 15 Oct 2024
Entity-Centric Reinforcement Learning for Object Manipulation from Pixels Dan Haramati Tal Daniel Aviv Tamar LM&Ro OffRL OCL 27 10 0 01 Apr 2024
Learning Reusable Manipulation Strategies Jiayuan Mao Joshua B. Tenenbaum Tomás Lozano-Pérez L. Kaelbling SSL 28 12 0 06 Nov 2023
Discovering Object-Centric Generalized Value Functions From Pixels Somjit Nath G. Subbaraj Khimya Khetarpal Samira Ebrahimi Kahou OCL 12 2 0 27 Apr 2023
Compositional Multi-Object Reinforcement Learning with Linear Relation Networks Davide Mambelli Frederik Trauble Stefan Bauer Bernhard Schölkopf Francesco Locatello OCL 28 17 0 31 Jan 2022
Self-supervised Reinforcement Learning with Independently Controllable Subgoals Andrii Zadaianchuk Georg Martius Fanny Yang SSL 57 16 0 09 Sep 2021