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1909.07483
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The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition
12 September 2019
Benjamin Beyret
José Hernández-Orallo
Lucy G. Cheke
Marta Halina
Murray Shanahan
Matthew Crosby
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Papers citing
"The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition"
12 / 12 papers shown
Title
Discretization of continuous input spaces in the hippocampal autoencoder
A. F. Amil
Ismael T. Freire
P. Verschure
49
3
0
23 May 2024
Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds
Joshua Albrecht
Abraham J. Fetterman
Bryden Fogelman
Ellie Kitanidis
Bartosz Wróblewski
...
Michael Rosenthal
Maksis Knutins
Zachary Polizzi
James B. Simon
Kanjun Qiu
OffRL
80
23
0
24 Oct 2022
OPEn: An Open-ended Physics Environment for Learning Without a Task
Chuang Gan
Abhishek Bhandwaldar
Antonio Torralba
J. Tenenbaum
Phillip Isola
LRM
195
4
0
13 Oct 2021
Extending Environments To Measure Self-Reflection In Reinforcement Learning
S. Alexander
Michael Castaneda
K. Compher
Oscar Martinez
68
6
0
13 Oct 2021
Capturing the objects of vision with neural networks
B. Peters
N. Kriegeskorte
OCL
83
61
0
07 Sep 2021
A learning gap between neuroscience and reinforcement learning
Samuel T. Wauthier
Pietro Mazzaglia
Ozan Çatal
Cedric De Boom
Tim Verbelen
Bart Dhoedt
31
3
0
22 Apr 2021
The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI
Chuang Gan
Siyuan Zhou
Jeremy Schwartz
S. Alter
Abhishek Bhandwaldar
...
Daniel L. K. Yamins
J. DiCarlo
Josh H. McDermott
Antonio Torralba
J. Tenenbaum
LM&Ro
113
81
0
25 Mar 2021
Guided Exploration with Proximal Policy Optimization using a Single Demonstration
Gabriele Libardi
Gianni De Fabritiis
58
24
0
07 Jul 2020
Neuroevolution of Self-Interpretable Agents
Yujin Tang
Duong Nguyen
David R Ha
125
113
0
18 Mar 2020
Adapting to Unseen Environments through Explicit Representation of Context
C. Tutum
Risto Miikkulainen
16
0
0
13 Feb 2020
Leveraging Procedural Generation to Benchmark Reinforcement Learning
K. Cobbe
Christopher Hesse
Jacob Hilton
John Schulman
99
557
0
03 Dec 2019
Increasing Generality in Machine Learning through Procedural Content Generation
S. Risi
Julian Togelius
67
126
0
29 Nov 2019
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