Cognitive development concerns the evolution of human mental capabilities through experience earned during life. Important features needed to accomplish this target are the self-generation of motivations and goals as well as the development of complex behaviors consistent with these goals. Our target is to build such a bio-inspired cognitive architecture for situated agents, capable of integrating new sensing data from any source. Based on neuroscience assessed concepts, as neural plasticity and neural coding, we show how a categorization module built on cascading classifiers is able to interpret different sensing data. Moreover, we see how to give a biological interpretation to our classification model using the winner-take-all paradigm.

Bio-inspired Classification in the Architecture of Situated Agents, 2016.

Bio-inspired Classification in the Architecture of Situated Agents

MANZOTTI, RICCARDO
2016-01-01

Abstract

Cognitive development concerns the evolution of human mental capabilities through experience earned during life. Important features needed to accomplish this target are the self-generation of motivations and goals as well as the development of complex behaviors consistent with these goals. Our target is to build such a bio-inspired cognitive architecture for situated agents, capable of integrating new sensing data from any source. Based on neuroscience assessed concepts, as neural plasticity and neural coding, we show how a categorization module built on cascading classifiers is able to interpret different sensing data. Moreover, we see how to give a biological interpretation to our classification model using the winner-take-all paradigm.
Inglese
2016
Menegatti, E.; Michael, N.; Berns, K.; Yamaguchi, H.
Intelligent Autonomous Systems 13
1
1
14
14
978-3-319-08338-4
Germany
Springer
comitato scientifico
internazionale
A stampa
Settore M-FIL/01 - Filosofia Teoretica
6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10808/22491
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