Learning Causal State Representations of Partially Observable Environments

25 June 2019

Papers citing "Learning Causal State Representations of Partially Observable Environments"

7 / 7 papers shown

Title
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 17 20 0 17 Jan 2024
Common Information based Approximate State Representations in Multi-Agent Reinforcement Learning Shitao Xiao V. Subramanian 13 9 0 25 Oct 2021
Context-Specific Representation Abstraction for Deep Option Learning Marwa Abdulhai Dong-Ki Kim Matthew D Riemer Miao Liu Gerald Tesauro Jonathan P. How OffRL 29 9 0 20 Sep 2021
Meta-Adaptive Nonlinear Control: Theory and Algorithms Guanya Shi Kamyar Azizzadenesheli Michael O'Connell Soon-Jo Chung Yisong Yue 21 41 0 11 Jun 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 37 296 0 03 Mar 2021
Reinforcement Learning of Causal Variables Using Mediation Analysis Tue Herlau Rasmus Larsen OOD CML 21 8 0 29 Oct 2020
Meta-trained agents implement Bayes-optimal agents Vladimir Mikulik Grégoire Delétang Tom McGrath Tim Genewein Miljan Martic Shane Legg Pedro A. Ortega OOD FedML 27 40 0 21 Oct 2020