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Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios
Published on: August 4, 2023
Toward biologically plausible artificial vision
1Department of Philosophy, Philosophy-Neuroscience-Psychology Program, Washington University in St. Louis, St. Louis, MO, USA w.mason@wustl.eduhttp://www.masonwestfall.com.
Abstract:
Quilty-Dunn et al. argue that deep convolutional neural networks (DCNNs) optimized for image classification exemplify structural disanalogies to human vision. A different kind of artificial vision - found in reinforcement-learning agents navigating artificial three-dimensional environments - can be expected to be more human-like. Recent work suggests that language-like representations substantially improves these agents' performance, lending some indirect support to the language-of-thought hypothesis (LoTH).
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