Abstract
Direct connnectionist modeling of higher cognitive functions, such as language understanding, is impractical. This chapter describes a principled multi-layer architecture that supports AI style computational modeling while preserving the biological plausibility of structured connectionist models. As an example, the connectionist realization of Bayesian model merging as recruitment learning is presented.
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Feldman, J., Bailey, D. (2000). Layered Hybrid Connectionist Models for Cognitive Science. In: Wermter, S., Sun, R. (eds) Hybrid Neural Systems. Hybrid Neural Systems 1998. Lecture Notes in Computer Science(), vol 1778. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10719871_2
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DOI: https://doi.org/10.1007/10719871_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67305-7
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