The impact of population composition for cooperation emergence in evolutionary robotics

  • Rodrigo Palacios-Leyva Artificial Intelligence Research Center. University of Veracruz
  • Fernando Aldana-Franco Artificial Intelligence Research Center. University of Veracruz.
  • Bruno Lara-Guzmán Sciences Department, Autonomous University of Morelos
  • Fernando Montes-González Artificial Intelligence Research Center. University of Veracruz
Keywords: Evolutionary Robotics, Neural Networks, Communication Signals, FARSA, Marxbot

Abstract

Communication is an important tool for evolutionary robotics. Some important aspects are the emergence of signals, the environment, and manipulation of social and evolutionary variables. In this paper we focus on social aspects related to exploration in poisoned and food environments. These aspects are as follows: a) intermediate levels of heterogeneity in population of evolutionary robots, and b) cooperation of robots for fitness contribution to regulate the emergence of communication signals. The FARSA simulator and Marxbot robot are used in order to optimize the weights of neural networks using a steady state genetic algorithm. A basic communication system is developed based on color LEDs and linear cameras.

Published
2018-01-09
How to Cite
Palacios-Leyva, R., Aldana-Franco, F., Lara-Guzmán, B., & Montes-González, F. (2018). The impact of population composition for cooperation emergence in evolutionary robotics. International Journal of Combinatorial Optimization Problems and Informatics, 8(3), 20-32. Retrieved from https://www.ijcopi.org/index.php/ojs/article/view/15
Section
Articles