Title
Selection for reinforcement-free learning ability as an organizing factor in the evolution of cognition
Abstract
This research explores the relation between environmental structure and neurocognitive structure. We hypothesize that selection pressure on abilities for efficient learning (especially in settings with limited or no reward information) translates into selection pressure on correspondence relations between neurocognitive and environmental structure, since such correspondence allows for simple changes in the environment to be handled with simple learning updates in neurocognitive structure. We present a model in which a simple formof reinforcement-free learning is evolved in neural networks using neuromodulation and analyze the effect this selection for learning ability has on the virtual species' neural organization. We find a higher degree of organization than in a control population evolved 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, the Baldwin effect, and other interactions between adaptation processes.
Year
DOI
Venue
2013
10.1155/2013/841646
Adv. Artificial Intellegence
Keywords
Field
DocType
simple learning updates,observed neural structure,environmental structure,environmental complexity thesis,neural organization,neural network,neurocognitive structure,selection pressure,simple formof reinforcement-free learning,efficient learning
Population,Computer science,Artificial intelligence,Artificial neural network,Cognition,Reinforcement,Neurocognitive,Machine learning,Baldwin effect
Journal
Volume
Issue
Citations 
2013,
Issue-in-Progress
3
PageRank 
References 
Authors
0.45
11
3
Name
Order
Citations
PageRank
Solvi Arnold1152.40
Reiji Suzuki210533.02
Takaya Arita313042.34