Evolving artificial minds and brains

In Drew Khlentzos & Andrea Schalley (eds.), Mental States Volume 1: Evolution, function, nature. John Benjamins (2007)

Authors
Pete Mandik
William Paterson University of New Jersey
Abstract
We explicate representational content by addressing how representations that ex- plain intelligent behavior might be acquired through processes of Darwinian evo- lution. We present the results of computer simulations of evolved neural network controllers and discuss the similarity of the simulations to real-world examples of neural network control of animal behavior. We argue that focusing on the simplest cases of evolved intelligent behavior, in both simulated and real organisms, reveals that evolved representations must carry information about the creature’s environ- ments and further can do so only if their neural states are appropriately isomor- phic to environmental states. Further, these informational and isomorphism rela- tions are what are tracked by content attributions in folk-psychological and cognitive scientific explanations of these intelligent behaviors.
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References found in this work BETA

Thinking About Mechanisms.Peter K. Machamer, Lindley Darden & Carl F. Craver - 2000 - Philosophy of Science 67 (1):1-25.
Intelligence Without Representation.Rodney Brooks - 1991 - Artificial Intelligence 47 (1--3):139-159.
Role Functions, Mechanisms, and Hierarchy.Carl F. Craver - 2001 - Philosophy of Science 68 (1):53-74.
Scientific Representation: Against Similarity and Isomorphism.Mauricio Sua´rez - 2003 - International Studies in the Philosophy of Science 17 (3):225-244.

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Citations of this work BETA

Constructing a Philosophy of Science of Cognitive Science.William Bechtel - 2009 - Topics in Cognitive Science 1 (3):548-569.
Constructing a Philosophy of Science of Cognitive Science.William Bechtel - 2009 - Topics in Cognitive Science 1 (3):548-569.
Now or Never: How Consciousness Represents Time☆.Paula Droege - 2009 - Consciousness and Cognition 18 (1):78-90.

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