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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Levels Of Conscious And Unconscious Anticipatory Behaviour For

Artificial Creatures

Authors:

Pavel Nahodil

Published in:

 

(2011).ECMS 2011 Proceedings edited by: T. Burczynski, J. Kolodziej, A. Byrski, M. Carvalho. European Council for Modeling and Simulation. doi:10.7148/2011 

 

ISBN: 978-0-9564944-2-9

 

25th European Conference on Modelling and Simulation,

Jubilee Conference

Krakow, June 7-10, 2011

 

Citation format:

Nahodil, P. (2011). Levels Of Conscious And Unconscious Anticipatory Behaviour For Artificial Creatures. ECMS 2011 Proceedings edited by: T. Burczynski, J. Kolodziej, A. Byrski, M. Carvalho (pp. 98-104). European Council for Modeling and Simulation. doi:10.7148/2011-0098-0104

DOI:

http://dx.doi.org/10.7148/2011-0098-0104

Abstract:

Recently, anticipation and anticipatory learning systems have gained increasing attention in the field. The interest of researchers in anticipation did not started over night. Anticipation observed in the animals combined with the multi-agent systems and artificial life gave birth to the anticipatory behaviour. This is broad multidisciplinary topic, but there are little thoughts on relation of anticipation with the reactive behaviour, the similarities and where the boundary is. Reactive behaviour is still considered as the exact opposite for the anticipatory one. It was shown by us that reactive and anticipatory behaviour can be combined. Designed multi-level anticipatory behaviour approach is based on the current understanding of anticipation from both the artificial intelligence and the biology point of view. Original thought is that we use not one but multiple levels of unconscious and conscious anticipation in a creature design. The topic is quite comprehensive and is out of scope of a single article to describe all 8 levels of the 8-factor anticipation framework design. The aim is not to extensively present all the achieved results but to demonstrate the thinking behind. Primary industrial application of this approach is intelligent robotics.

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