Bugs: A real-time adaptive network that responds to motion

Research output: Contribution to conferencePaper

Abstract

Summary form only given, as follows. Bugs is an artificial neural system which detects motion in an external environment and can be trained by a teacher to react according to a desired strategy. System elements are a hard-wired motion detection network and an adaptive controller network. The motion detection net is based on a model of motion-sensitive ganglia found in rabbit eyes, while the controller learns strategies from a teacher in the form of finite-state transitions. Bugs's subnetworks are integrated by continuous-time dynamics, and elements are synchronized through simple time-scaling parameters. The author reports two experiments in which Bugs learned quite different responses to moving objects.

Original languageEnglish (US)
Number of pages1
StatePublished - Dec 1 1989
Externally publishedYes
EventIJCNN International Joint Conference on Neural Networks - Washington, DC, USA
Duration: Jun 18 1989Jun 22 1989

Other

OtherIJCNN International Joint Conference on Neural Networks
CityWashington, DC, USA
Period6/18/896/22/89

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Winter, C. L. (1989). Bugs: A real-time adaptive network that responds to motion. Paper presented at IJCNN International Joint Conference on Neural Networks, Washington, DC, USA, .