University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Fast Learning of Stimulus-Response Associations

Fast Learning of Stimulus-Response Associations

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If you have a question about this talk, please contact Per Kristian Lehre.

Fast responses generated in time-constrained situations, such as a tennis game, are most likely based on a set on set of Stimulus-Response (SR) associations encoded along the shortest neural route linking visual input to motor output. Such SR associations can be learnt by various methods, e.g. from examples or from practice. However, the most fascinating and fastest method is to learn from verbal instructions. This fast process cannot be modelled by existing neural networks training algorithms. A new architecture and learning algorithm will be proposed to address this problem. Capabilities and open problems will be discussed, covering capacity, selectivity, dynamics, spiking neuron implementation and concepts of event-driven computing.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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