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Cognitive dynamics in neural systems: mathematical and computational modeling (CONAS 2012) (2011)| shared_uid | 1464 |
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| title | Cognitive dynamics in neural systems: mathematical and computational modeling (CONAS 2012) |
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| type | Atelier |
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| year | 2011 |
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| start_date | 2012/03/29 |
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| stop_date | 2012/03/30 |
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| schedule | 08h30-18h |
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| active | no |
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| website | http://conas2012.elis.ugent.be/ |
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| summary | Animals are proof that complete cognitive systems can be realized in neural substrates. It is thus natural that engineers from AI and machine learning have tried to design advanced cognitive systems on the basis of artificial neural networks. This has led to illuminating concepts and architectures in fields like computational linguistics, dynamic pattern recognition, autonomous agents, or evolutionary robotics. However, if one takes a close and critical look, one finds that nowhere do artificial systems close to biological levels of performance. One important cause for this gap is a lack of appropriate mathematical concepts. Biological neural systems are high-dimensional, nonlinear, heterogeneous, multiscale, nonstationary, stochastic, and heavily input-driven - a cocktail of properties which overwhelms current dynamical systems theory. Inasmuch as we do not possess mathematical models for such systems, we cannot understand them; and inasmuch as we do not understand, we cannot engineer.
This workshop will bring together researchers from three fields:
cognitive scientists, roboticists and machine learning engineers who develop complex, neural-network-based architectures;
computational neuroscientists who apply existing methods from dynamical systems theory to neural dynamics;
mathematicians who work on extensions of dynamical systems theory in directions that appear relevant for neurodynamics and complex neural learning architectures.
The purpose of the workshop is to create an awareness, across the three fields, of the general and fundamental methodological challenges that oppose easy progress; and at the same time, an appreciation of partial solutions, questions, and methods in the respective other fields which may inspire progress in one's own. |
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| responsibles | Jaeger, Müller, Dominey |
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