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A Top-Down Approach for a Synthetic Autobiographical Memory System
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
Vise andre og tillknytning
2015 (engelsk)Inngår i: BIOMIMETIC AND BIOHYBRID SYSTEMS, LIVING MACHINES 2015, Springer, 2015, 280-292 s.Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Autobiographical memory (AM) refers to the organisation of one's experience into a coherent narrative. The exact neural mechanisms responsible for the manifestation of AM in humans are unknown. On the other hand, the field of psychology has provided us with useful understanding about the functionality of a bio-inspired synthetic AM (SAM) system, in a higher level of description. This paper is concerned with a top-down approach to SAM, where known components and organisation guide the architecture but the unknown details of each module are abstracted. By using Bayesian latent variable models we obtain a transparent SAM system with which we can interact in a structured way. This allows us to reveal the properties of specific sub-modules and map them to functionality observed in biological systems. The top-down approach can cope well with the high performance requirements of a bio-inspired cognitive system. This is demonstrated in experiments using faces data.

sted, utgiver, år, opplag, sider
Springer, 2015. 280-292 s.
Serie
Lecture Notes in Artificial Intelligence, ISSN 0302-9743 ; 9222
Emneord [en]
Synthetic autobiographical memory, Hippocampus, Robotics, Deep Gaussian process, MRD
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-177974DOI: 10.1007/978-3-319-22979-9_28ISI: 000364183200028Scopus ID: 2-s2.0-84947125286ISBN: 978-3-319-22979-9; 978-3-319-22978-2 (tryckt)OAI: oai:DiVA.org:kth-177974DiVA: diva2:875974
Konferanse
4th International Conference on Biomimetic and Biohybrid Systems (Living Machines), JUL 28-31, 2015, Barcelona, SPAIN
Merknad

QC 20151202

Tilgjengelig fra: 2015-12-02 Laget: 2015-11-30 Sist oppdatert: 2018-01-10bibliografisk kontrollert

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Totalt: 35 treff
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