Adaptive network that flees pursuit

C. L. Winter

doi:10.1016/0893-6080(88)90395-4

Adaptive network that flees pursuit

Research output: Contribution to journal › Conference article › peer-review

Abstract

We describe a hierarchical artificial neural system (ANS) that learns to flee predators in a world without obstacles. The ANS is composed of a motion detection network (MD) an adaptive controller and body. Currently we simulate the activity of the body. The network operates in continuous time and is controlled solely through the activities of nodes. The controller obtains sensory information from MD in the form of reduced resolution maps of motion in the prey's visual field and determines a desirable next position by evaluating both motion information and the prey's current position as obtained from the body. The next position is passed as a goal, or instruction, to the body which moves accordingly.

Original language	English (US)
Pages (from-to)	367
Number of pages	1
Journal	Neural Networks
Volume	1
Issue number	1 SUPPL
DOIs	https://doi.org/10.1016/0893-6080(88)90395-4
State	Published - 1988
Event	International Neural Network Society 1988 First Annual Meeting - Boston, MA, USA Duration: Sep 6 1988 → Sep 10 1988

ASJC Scopus subject areas

Cognitive Neuroscience
Artificial Intelligence

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10.1016/0893-6080(88)90395-4

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title = "Adaptive network that flees pursuit",

abstract = "We describe a hierarchical artificial neural system (ANS) that learns to flee predators in a world without obstacles. The ANS is composed of a motion detection network (MD) an adaptive controller and body. Currently we simulate the activity of the body. The network operates in continuous time and is controlled solely through the activities of nodes. The controller obtains sensory information from MD in the form of reduced resolution maps of motion in the prey's visual field and determines a desirable next position by evaluating both motion information and the prey's current position as obtained from the body. The next position is passed as a goal, or instruction, to the body which moves accordingly.",

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AB - We describe a hierarchical artificial neural system (ANS) that learns to flee predators in a world without obstacles. The ANS is composed of a motion detection network (MD) an adaptive controller and body. Currently we simulate the activity of the body. The network operates in continuous time and is controlled solely through the activities of nodes. The controller obtains sensory information from MD in the form of reduced resolution maps of motion in the prey's visual field and determines a desirable next position by evaluating both motion information and the prey's current position as obtained from the body. The next position is passed as a goal, or instruction, to the body which moves accordingly.

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DO - 10.1016/0893-6080(88)90395-4

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SN - 0893-6080

VL - 1

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JO - Neural Networks

JF - Neural Networks

IS - 1 SUPPL

T2 - International Neural Network Society 1988 First Annual Meeting

Y2 - 6 September 1988 through 10 September 1988

ER -

Adaptive network that flees pursuit

Abstract

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