Evolving a neural model of insect path integration

Haferlach, Thomas and Wessnitzer, Jan and Mangan, Michael and Webb, Barbara (2007) Evolving a neural model of insect path integration. Adaptive Behavior, 15 (3). pp. 273-287. ISSN 1059-7123

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Abstract

Path integration is an important navigation strategy in many animal species. We use a genetic algorithm to evolve a novel neural model of path integration, based on input from cells that encode the heading of the agent in a manner comparable to the polarization-sensitive interneurons found in insects. The home vector is encoded as a population code across a circular array of cells that integrate this input. This code can be used to control return to the home position. We demonstrate the capabilities of the network under noisy conditions in simulation and on a robot.

Keywords:Path integration, Direction cells, Genetic algorithm, Neural network, Simulation, Robot
Subjects:D Veterinary Sciences, Agriculture and related subjects > D300 Animal Science
G Mathematical and Computer Sciences > G730 Neural Computing
Divisions:College of Science > School of Computer Science
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http://purl.org/dc/terms/isReferencedbyhttp://eprints.lincoln.ac.uk/23578/
ID Code:23574
Deposited On:03 Aug 2016 12:00

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