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Probabilistic Control and Swarm Dynamics in Mobile Robots and Ants
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Author(s): Eugene Kagan (The Weizmann Institute of Science, Israel), Alexander Rybalov (Jerusalem College of Technology, Israel), Alon Sela (Tel-Aviv University, Israel), Hava Siegelmann (University of Massachusetts at Amherst, USA)and Jennie Steshenko (University of Massachusetts at Amherst, USA)
Copyright: 2014
Pages: 37
Source title:
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
Source Author(s)/Editor(s): Shafiq Alam (University of Auckland, New Zealand), Gillian Dobbie (University of Auckland, New Zealand), Yun Sing Koh (University of Auckland, New Zealand)and Saeed ur Rehman (Unitec Institute of Technology, New Zealand)
DOI: 10.4018/978-1-4666-6078-6.ch002
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Abstract
The chapter considers the method of probabilistic control of mobile robots navigating in random environments and mimicking the foraging activity of ants, which is widely accepted as optimal with respect to the environmental conditions. The control is based on the Tsetlin automaton, which is a minimal automaton demonstrating an expedient behavior in random environments. The suggested automaton implements probability-based aggregators, which form a complete algebraic system and support an activity of the automaton over non-Boolean variables. The considered mobile agents are based on the Braitenberg vehicles equipped with four types of sensors, which mimic the basic sensing abilities of ants: short- and long-distance sensing of environmental states, sensing of neighboring agents, and sensing the pheromone traces. Numerical simulations demonstrate that the foraging behavior of the suggested mobile agents, running both individually and in groups, is statistically indistinguishable from the foraging behavior of real ants observed in laboratory experiments.
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