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pro vyhledávání: '"Prescott, Tony"'
The rising successes of RL are propelled by combining smart algorithmic strategies and deep architectures to optimize the distribution of returns and visitations over the state-action space. A quantitative framework to compare the learning processes
Externí odkaz:
http://arxiv.org/abs/2402.09113
Hippocampal reverse replay is thought to contribute to learning, and particularly reinforcement learning, in animals. We present a computational model of learning in the hippocampus that builds on a previous model of the hippocampal-striatal network
Externí odkaz:
http://arxiv.org/abs/2102.11914
Autor:
Prescott, Tony J.1 (AUTHOR) t.j.prescott@sheffield.ac.uk, Montes González, Fernando M.2 (AUTHOR) fmontes@uv.mx, Gurney, Kevin3 (AUTHOR) k.gurney@sheffield.ac.uk, Humphries, Mark D.4 (AUTHOR) mark.humphries@nottingham.ac.uk, Redgrave, Peter3 (AUTHOR) p.redgrave@sheffield.ac.uk
Publikováno v:
Biomimetics (2313-7673). Mar2024, Vol. 9 Issue 3, p139. 34p.
Akademický článek
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Publikováno v:
In Journal of Responsible Technology December 2022 12
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
Publikováno v:
Science Robotics; 10/30/2024, Vol. 9 Issue 95, p1-12, 12p
Autor:
Fernando, Samuel, Moore, Roger K., Cameron, David, Collins, Emily C., Millings, Abigail, Sharkey, Amanda J., Prescott, Tony J.
Automatic speech recognition (ASR) allows a natural and intuitive interface for robotic educational applications for children. However there are a number of challenges to overcome to allow such an interface to operate robustly in realistic settings,
Externí odkaz:
http://arxiv.org/abs/1611.02695