Using Broad Cognitive Models and Cognitive Robotics to Apply Computational Intelligence to Animal Cognition

Document Type: 
Article
Article Type: 
Theoretical
Disciplines: 
Artificial intelligence
Topics: 
Animal Cognition
Date of Issue: 
2008
Authors: 
Stan Franklin, Michael H. Ferkin
Editors: 
T. G. Smolinski, M. M. Milanova & A.-E. Hassanien
Title of Book: 
Applications of Computational Intelligence in Biology: Current Trends and Open Problems
Page Range: 
363-394
Publisher: 
Springer-Verlag
Official URL: 
http://ccrg.cs.memphis.edu/assets/papers/2009/BroadCognitiveModels.doc
Publish status: 
Published
Abstract: 
The field of animal cognition (comparative cognition, cognitive ethology), the study of cognitive modules and processes in the domain of ecologically relevant animal behaviors, has become mainstream in biology. The field has its own journals, books, organization and conferences. As do other scientists, cognitive ethologists employ conceptual models, mathematical models and sometime computational models. Most of these models, of all three types, are narrow in scope, modeling only one or a few cognitive processes. This position chapter advocates, as an additional strategy, studying animal cognition by means of computational control architectures based on biologically and psychologically inspired, broad, integrative, hybrid models of cognition. The LIDA model is one such model. In particular, the LIDA model fleshes out a theory of animal cognition, and underlies a proposed ontology for its study. Using the LIDA model, animal experiments can be replicated in artificial environments by means of virtual software agents controlled by such architectures. Given sufficiently capable sensors and effectors, such experiments could be replicated in real environments using cognitive robots. Here we explore the possibility of such experiments using a virtual or a robotic vole to replicate, and to predict, the behavior of live voles, thus applying computational intelligence to cognitive ethology.
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