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Conference Paper

Multisensory Perceptual Discrimination in Evolved Networks and Agents

MPS-Authors
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Rohde,  M
Research Group Multisensory Perception and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://dblp.uni-trier.de/db/conf/alife/alife2010.html
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ALife-XII-2010-Rohde_6729[0].pdf
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Citation

Rohde, M. (2010). Multisensory Perceptual Discrimination in Evolved Networks and Agents. In H. Fellermann, M. Dörr, M. Hanczyc, L. Ladegaard Laursen, S. Maurer, D. Merkle, et al. (Eds.), Artificial Life XII (ALIFE 2010) (pp. 607-614). Cambridge, MA, USA: MIT Press.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-BEC2-D
Abstract
The fact that humans and animals have several sensory modalities and use them together to make sense of the world imbues their behaviour with an immense richness and robustness. In this study, recurrent neural networks and minimal agents with active vision are evolved for a perceptual discrimination task (unimodal and bimodal). The purpose of this
study is mainly exploratory: to test which of the characteristics
of human perceptual discrimination evolve easily (with a focus on statistically optimal integration), how they are realised and what active perception does in this process. Whilst some of the systems evolved to perform perceptual discrimination well, they did not conform to the predictions from
statistical optimality. Analyses of the systems point towards a number of relevant issues, noticeably towards the lack of a good account of ‘unimodality’ in existing models of multisensory perception.