Adaptive network that flees pursuit

Research output: Contribution to journalConference articlepeer-review


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 languageEnglish (US)
Pages (from-to)367
Number of pages1
JournalNeural Networks
Issue number1 SUPPL
StatePublished - 1988
EventInternational Neural Network Society 1988 First Annual Meeting - Boston, MA, USA
Duration: Sep 6 1988Sep 10 1988

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence


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