Success Rate of Creatures Crossing a Highway as a Function of Model Parameters

In modeling swarms of autonomous robots, individual robots may be identified as cognitive agents. The authors describe a model of population of simple cognitive agents, naïve creatures, learning to safely cross a cellular automaton based highway. These creatures have the ability to learn from each other by evaluating if creatures in the past were successful in crossing the highway for their current situation. The creatures use “observational social learning” mechanism in their decision to cross the highway or not. The model parameters heavily influence the learning outcomes examined through the collected simulation metrics. The authors study how these parameters, in particular the knowledge base, influence the creatures’ success rate of crossing the highway.

Language

  • English

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Filing Info

  • Accession Number: 01605525
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jun 6 2016 10:02AM