Zobrazeno 1 - 10
of 492
pro vyhledávání: '"Verschure, Paul F M J"'
The hippocampus has been associated with both spatial cognition and episodic memory formation, but integrating these functions into a unified framework remains challenging. Here, we demonstrate that forming discrete memories of visual events in spars
Externí odkaz:
http://arxiv.org/abs/2405.14600
State of the art deep reinforcement learning algorithms are sample inefficient due to the large number of episodes they require to achieve asymptotic performance. Episodic Reinforcement Learning (ERL) algorithms, inspired by the mammalian hippocampus
Externí odkaz:
http://arxiv.org/abs/2112.14734
The sample-inefficiency problem in Artificial Intelligence refers to the inability of current Deep Reinforcement Learning models to optimize action policies within a small number of episodes. Recent studies have tried to overcome this limitation by a
Externí odkaz:
http://arxiv.org/abs/2012.13779
Autor:
Blancas-Muñoz, Maria, Vouloutsi, Vasiliki, Zucca, Riccardo, Mura, Anna, Verschure, Paul F. M. J.
The kind of help a student receives during a task has been shown to play a significant role in their learning process. We designed an interaction scenario with a robotic tutor, in real-life settings based on an inquiry-based learning task. We aim to
Externí odkaz:
http://arxiv.org/abs/1806.07806
Autor:
Estefan, Daniel Pacheco, Zucca, Riccardo, Arsiwalla, Xerxes, Principe, Alessandro, Zhang, Hui, Rocamora, Rodrigo, Axmacher, Nikolai, Verschure, Paul F. M. J.
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2021 Mar 01. 118(10), 1-12.
Externí odkaz:
https://www.jstor.org/stable/27027546
What does the informational complexity of dynamical networked systems tell us about intrinsic mechanisms and functions of these complex systems? Recent complexity measures such as integrated information have sought to operationalize this problem taki
Externí odkaz:
http://arxiv.org/abs/1707.01446
Autor:
Moulin-Frier, Clément, Fischer, Tobias, Petit, Maxime, Pointeau, Grégoire, Puigbo, Jordi-Ysard, Pattacini, Ugo, Low, Sock Ching, Camilleri, Daniel, Nguyen, Phuong, Hoffmann, Matej, Chang, Hyung Jin, Zambelli, Martina, Mealier, Anne-Laure, Damianou, Andreas, Metta, Giorgio, Prescott, Tony J., Demiris, Yiannis, Dominey, Peter Ford, Verschure, Paul F. M. J.
Publikováno v:
IEEE Transactions on Cognitive and Developmental Systems 10 (4), 1005-1022, 2018
This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based
Externí odkaz:
http://arxiv.org/abs/1706.03661
Autor:
Moulin-Frier, Clément, Puigbò, Jordi-Ysard, Arsiwalla, Xerxes D., Sanchez-Fibla, Martì, Verschure, Paul F. M. J.
In this paper, we argue that the future of Artificial Intelligence research resides in two keywords: integration and embodiment. We support this claim by analyzing the recent advances of the field. Regarding integration, we note that the most impactf
Externí odkaz:
http://arxiv.org/abs/1704.01407
Publikováno v:
Advances in Neural Information Processing Systems, 29: 3828-3836, (2016)
How does our motor system solve the problem of anticipatory control in spite of a wide spectrum of response dynamics from different musculo-skeletal systems, transport delays as well as response latencies throughout the central nervous system? To a g
Externí odkaz:
http://arxiv.org/abs/1701.07775
Autor:
Freire, Ismael T., Guerrero-Rosado, Oscar, Amil, Adrián F., Verschure, Paul F. M. J., Fraboni, Federico, Sziebig, Gabor, Rosen, Patricia Helen
Publikováno v:
Frontiers in Robotics & AI; 2024, p1-19, 19p