Journal
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
Volume 367, Issue 1603, Pages 2686-2694Publisher
ROYAL SOC
DOI: 10.1098/rstb.2012.0213
Keywords
evolution of learning; comparative cognition; language acquisition; learning of structured data; data acquisition; innate template
Categories
Funding
- Israel Science Foundation [1312/11]
- NSF [IIS-0534064, IIS-0812045, IIS-0911036]
- AFOSR [FA9550-08-1-0438, FA9550-09-1-0266]
- ARO [W911NF-09-1-0281]
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1214844] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [812045] Funding Source: National Science Foundation
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A fundamental and frequently overlooked aspect of animal learning is its reliance on compatibility between the learning rules used and the attentional and motivational mechanisms directing them to process the relevant data (called here data-acquisition mechanisms). We propose that this coordinated action, which may first appear fragile and error prone, is in fact extremely powerful, and critical for understanding cognitive evolution. Using basic examples from imprinting and associative learning, we argue that by coevolving to handle the natural distribution of data in the animal's environment, learning and data-acquisition mechanisms are tuned jointly so as to facilitate effective learning using relatively little memory and computation. We then suggest that this coevolutionary process offers a feasible path for the incremental evolution of complex cognitive systems, because it can greatly simplify learning. This is illustrated by considering how animals and humans can use these simple mechanisms to learn complex patterns and represent them in the brain. We conclude with some predictions and suggested directions for experimental and theoretical work.
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