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Causal Reasoning from Meta-reinforcement Learning

Causal Reasoning from Meta-reinforcement Learning

23 January 2019
Ishita Dasgupta
Jane X. Wang
Silvia Chiappa
Jovana Mitrović
Pedro A. Ortega
David Raposo
Edward Hughes
Peter W. Battaglia
M. Botvinick
Z. Kurth-Nelson
    CML
    LRM
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Papers citing "Causal Reasoning from Meta-reinforcement Learning"

28 / 28 papers shown
Title
Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges
Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges
Miguel Arana-Catania
Weisi Guo
CML
30
0
0
13 May 2025
A Theoretical Analysis of Compositional Generalization in Neural Networks: A Necessary and Sufficient Condition
A Theoretical Analysis of Compositional Generalization in Neural Networks: A Necessary and Sufficient Condition
Yuanpeng Li
CoGe
143
0
0
05 May 2025
Systems with Switching Causal Relations: A Meta-Causal Perspective
Systems with Switching Causal Relations: A Meta-Causal Perspective
Moritz Willig
Tim Nelson Tobiasch
Florian Peter Busch
Jonas Seng
Devendra Singh Dhami
Kristian Kersting
CML
43
0
0
16 Oct 2024
Counterfactual Influence in Markov Decision Processes
Counterfactual Influence in Markov Decision Processes
M. Kazemi
Jessica Lally
Ekaterina Tishchenko
Hana Chockler
Nicola Paoletti
23
1
0
13 Feb 2024
Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought
  Reasoning
Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought Reasoning
Tinghui Zhu
Kai Zhang
Jian Xie
Yu-Chuan Su
LRM
28
14
0
31 Jan 2024
Passive learning of active causal strategies in agents and language
  models
Passive learning of active causal strategies in agents and language models
Andrew Kyle Lampinen
Stephanie C. Y. Chan
Ishita Dasgupta
A. Nam
Jane X. Wang
29
15
0
25 May 2023
On First-Order Meta-Reinforcement Learning with Moreau Envelopes
On First-Order Meta-Reinforcement Learning with Moreau Envelopes
Taha Toghani
Sebastian Perez-Salazar
César A. Uribe
29
2
0
20 May 2023
Meta-Learned Models of Cognition
Meta-Learned Models of Cognition
Marcel Binz
Ishita Dasgupta
A. Jagadish
M. Botvinick
Jane X. Wang
Eric Schulz
30
25
0
12 Apr 2023
Q-Cogni: An Integrated Causal Reinforcement Learning Framework
Q-Cogni: An Integrated Causal Reinforcement Learning Framework
C. Cunha
Wei Liu
T. French
Ajmal Saeed Mian
18
1
0
26 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality
A Survey of Methods, Challenges and Perspectives in Causality
Gael Gendron
Michael Witbrock
Gillian Dobbie
OOD
AI4CE
CML
29
12
0
01 Feb 2023
A Short Survey of Systematic Generalization
A Short Survey of Systematic Generalization
Yuanpeng Li
AI4CE
38
1
0
22 Nov 2022
Intelligent Computing: The Latest Advances, Challenges and Future
Intelligent Computing: The Latest Advances, Challenges and Future
Shiqiang Zhu
Ting Yu
Tao Xu
Hongyang Chen
Schahram Dustdar
...
Tariq S. Durrani
Huaimin Wang
Jiangxing Wu
Tongyi Zhang
Yunhe Pan
AI4CE
27
117
0
21 Nov 2022
Using Contrastive Samples for Identifying and Leveraging Possible Causal
  Relationships in Reinforcement Learning
Using Contrastive Samples for Identifying and Leveraging Possible Causal Relationships in Reinforcement Learning
H. Khadilkar
Hardik Meisheri
OffRL
18
1
0
28 Oct 2022
On a Built-in Conflict between Deep Learning and Systematic
  Generalization
On a Built-in Conflict between Deep Learning and Systematic Generalization
Yuanpeng Li
OOD
45
0
0
24 Aug 2022
Using cognitive psychology to understand GPT-3
Using cognitive psychology to understand GPT-3
Marcel Binz
Eric Schulz
ELM
LLMAG
250
440
0
21 Jun 2022
On the Generalization and Adaption Performance of Causal Models
On the Generalization and Adaption Performance of Causal Models
Nino Scherrer
Anirudh Goyal
Stefan Bauer
Yoshua Bengio
Nan Rosemary Ke
CML
OOD
BDL
TTA
31
8
0
09 Jun 2022
Active learning of causal probability trees
Active learning of causal probability trees
Tue Herlau
CML
15
0
0
17 May 2022
Counterfactual harm
Counterfactual harm
Jonathan G. Richens
R. Beard
Daniel H. Thompson
26
27
0
27 Apr 2022
Learning Causal Overhypotheses through Exploration in Children and
  Computational Models
Learning Causal Overhypotheses through Exploration in Children and Computational Models
Eliza Kosoy
Adrian Liu
Jasmine Collins
David M. Chan
Jessica B. Hamrick
Nan Rosemary Ke
Sandy H Huang
Bryanna Kaufmann
John F. Canny
Alison Gopnik
CML
22
9
0
21 Feb 2022
Human-Level Reinforcement Learning through Theory-Based Modeling,
  Exploration, and Planning
Human-Level Reinforcement Learning through Theory-Based Modeling, Exploration, and Planning
Pedro Tsividis
J. Loula
Jake Burga
Nathan Foss
Andres Campero
Thomas Pouncy
S. Gershman
J. Tenenbaum
LM&Ro
24
43
0
27 Jul 2021
Systematic Evaluation of Causal Discovery in Visual Model Based
  Reinforcement Learning
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
Nan Rosemary Ke
Aniket Didolkar
Sarthak Mittal
Anirudh Goyal
Guillaume Lajoie
Stefan Bauer
Danilo Jimenez Rezende
Yoshua Bengio
Michael C. Mozer
C. Pal
CML
29
54
0
02 Jul 2021
Did I do that? Blame as a means to identify controlled effects in
  reinforcement learning
Did I do that? Blame as a means to identify controlled effects in reinforcement learning
Oriol Corcoll
Youssef Mohamed
Raul Vicente
18
3
0
01 Jun 2021
Reinforcement Learning of Causal Variables Using Mediation Analysis
Reinforcement Learning of Causal Variables Using Mediation Analysis
Tue Herlau
Rasmus Larsen
OOD
CML
29
8
0
29 Oct 2020
Learning Neural Causal Models from Unknown Interventions
Learning Neural Causal Models from Unknown Interventions
Nan Rosemary Ke
O. Bilaniuk
Anirudh Goyal
Stefan Bauer
Hugo Larochelle
Bernhard Schölkopf
Michael C. Mozer
C. Pal
Yoshua Bengio
CML
OOD
41
168
0
02 Oct 2019
Meta-learning of Sequential Strategies
Meta-learning of Sequential Strategies
Pedro A. Ortega
Jane X. Wang
Mark Rowland
Tim Genewein
Z. Kurth-Nelson
...
Yee Whye Teh
H. V. Hasselt
Nando de Freitas
M. Botvinick
Shane Legg
OffRL
22
96
0
08 May 2019
Where Do Human Heuristics Come From?
Where Do Human Heuristics Come From?
Marcel Binz
Dominik M. Endres
16
0
0
20 Feb 2019
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Yoshua Bengio
T. Deleu
Nasim Rahaman
Nan Rosemary Ke
Sébastien Lachapelle
O. Bilaniuk
Anirudh Goyal
C. Pal
CML
OOD
46
332
0
30 Jan 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
338
11,684
0
09 Mar 2017
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