Proceedings of the 3d Conference on Artificial General Intelligence (2010)

An Artificial Intelligence Model that Combines Spatial and Temporal Perception

Authors
Jianglong Nan, Fintan Costello
Corresponding Author
Jianglong Nan
Available Online June 2010.
DOI
10.2991/agi.2010.38How to use a DOI?
Abstract

This paper proposes a continuous-time machine learning model that learns the chronological relationships and the intervals between events, stores and organises the learnt knowledge in different levels of abstraction in a network, and makes predictions about future events. The acquired knowledge is represented in a categorisation-like manner, in which events are categorised into categories of different levels. This inherently facilitates the categorisation of static items and leads to a general approach to both spatial and temporal perception. The paper presents the approach and a demonstration showing how it works.

Copyright
© 2010, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3d Conference on Artificial General Intelligence (2010)
Series
Advances in Intelligent Systems Research
Publication Date
June 2010
ISBN
978-90-78677-36-9
ISSN
1951-6851
DOI
10.2991/agi.2010.38How to use a DOI?
Copyright
© 2010, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jianglong Nan
AU  - Fintan Costello
PY  - 2010/06
DA  - 2010/06
TI  - An Artificial Intelligence Model that Combines Spatial and Temporal Perception
BT  - Proceedings of the 3d Conference on Artificial General Intelligence (2010)
PB  - Atlantis Press
SP  - 176
EP  - 181
SN  - 1951-6851
UR  - https://doi.org/10.2991/agi.2010.38
DO  - 10.2991/agi.2010.38
ID  - Nan2010/06
ER  -