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A Model for Foraging Ants, Controlled by Spiking Neural Networks and Double Pheromones by Jimenez-Romero, Cristian; Sousa-Rodrigues, David; Johnson, Jeffrey H.; Ramos, Vitorino is a scholarly article available to read on EtoBox.

What is A Model for Foraging Ants, Controlled by Spiking Neural Networks and Double Pheromones about?

A model of an Ant System where ants are controlled by a spiking neural circuit and a second order pheromone mechanism in a foraging task is presented. A neural circuit is trained for individual ants and subsequently the ants are exposed to a virtual environment where a swarm of ants performed a resource foraging task. The model comprises an associative and unsupervised learning strategy for the neural circuit of the ant. The neural circuit adapts to the environment by means of classical conditioning. The initially unknown environment includes different types of stimuli representing food and obstacles which, when they come in direct contact with the ant, elicit a reflex response in the motor neural system of the ant: moving towards or away from the source of the stimulus. The ants are released on a landscape with multiple food sources where one ant alone would have difficulty harvesting the landscape to maximum efficiency. The introduction of a double pheromone mechanism yields better results than traditional ant colony optimization strategies. Traditional ant systems include mainly a positive reinforcement pheromone. This approach uses a second pheromone that acts as a marker for f

Author

Jimenez-Romero, Cristian; Sousa-Rodrigues, David; Johnson, Jeffrey H.; Ramos, Vitorino

Published

2015

Language

EN