DocumentCode :
2306999
Title :
Neuro-cognitive organization as a side-effect of the evolution of learning ability
Author :
Arnold, S.F.
Author_Institution :
Dept. of Complex Syst. Sci., Nagoya Univ., Nagoya, Japan
fYear :
2011
fDate :
11-15 April 2011
Firstpage :
100
Lastpage :
107
Abstract :
This research explores the relation between environmental organization and cognitive organization. We hypothesize that selection pressure on learning ability indirectly causes selection pressure on alignment of neuro-cognitive and environmental structure, since such alignment implies that small changes in the environment can be handled with small changes in the implementation of behaviour. We indicate reinforcement-free types of learning ability as most strongly reliant on such alignment. We present a model in which a simple form of reinforcement-free learning is evolved in neural networks, and analyze the effect this has on the virtual species´ neural organization. We find a higher degree of organization than in a control population without learning ability, and discuss the relation between the observed neural structure and the environmental structure. We discuss our findings in the context of the environmental complexity thesis and the Baldwin effect.
Keywords :
cognition; cognitive systems; learning (artificial intelligence); neural nets; Baldwin effect; cognitive organization; environmental complexity; environmental organization; learning ability evolution; neural networks; neurocognitive organization; reinforcement-free learning; virtual species; Artificial neural networks; Evolution (biology); Learning systems; Machine learning; Neurons; Organisms; Organizations; Baldwin effect; Evolution of learning ability; environmental complexity thesis; evolution of mind; neuromodulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Life (ALIFE), 2011 IEEE Symposium on
Conference_Location :
Paris
ISSN :
2160-6374
Print_ISBN :
978-1-61284-062-8
Type :
conf
DOI :
10.1109/ALIFE.2011.5954646
Filename :
5954646
Link To Document :
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