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.
|Title of host publication||Biologically-Inspired Techniques for Knowledge Discovery and Data Mining|
|Number of pages||37|
|ISBN (Print)||1466660783, 9781466660786|
|State||Published - 31 May 2014|
Bibliographical noteFunding Information:
This research was supported by a grant from the Office of Education (OEG-3-71-0122).
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