Abstract
Manual design of self-organized behavioral control for swarms of robots is a complex task. Neuroevolution has proved a viable alternative given its capacity to automatically synthesize controllers. In this paper, we introduce the concept of Genome Variations (GV) in the neuroevolution of behavioral control for robotic swarms. In an evolutionary setup with GV, a slight mutation is applied to the evolving neural network parameters before they are copied to the robots in a swarm. The genome variation is individual to each robot, thereby generating a slightly heterogeneous swarm. GV represents a novel approach to the evolution of robust behaviors, expected to generate more stable and robust individual controllers, and benefit swarm behaviors that can deal with small heterogeneities in the behavior of other members in the swarm. We conduct experiments using an aggregation task, and compare the evolved solutions to solutions evolved under ideal, noise-free conditions, and to solutions evolved with traditional sensor noise.
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Bäck, T., Schwefel, H.P.: An overview of evolutionary algorithms for parameter optimization. Evolutionary Computation 1(1), 1–23 (1993)
Baldassarre, G., Nolfi, S., Parisi, D.: Evolving mobile robots able to display collective behaviors. Artificial Life 9(3), 255–267 (2003)
Beer, R.D., Gallagher, J.C.: Evolving Dynamical Neural Networks for Adaptive Behavior. Adaptive Behavior 1(1), 91–122 (1992)
Bongard, J.C.: Evolutionary robotics. Communications of the ACM 56(8), 74–83 (2013)
Brooks, R.A.: Elephants don’t play chess. Robotics and Autonomous Systems 6(1), 3–15 (1990)
Camazine, S., Deneubourg, J.L., Franks, N.R., Sneyd, J., Theraulaz, G., Bonabeau, E.: Self-organisation in biological systems. Princeton University Press (2001)
Christensen, A.L., Oliveira, S., Postolache, O., de Oliveira, M.J., Sargento, S., Santana, P., Nunes, L., Velez, F., Sebastião, P., Costa, V., Duarte, M., Gomes, J., Rodrigues, T., Silva, F.: Design of communication and control for swarms of aquatic surface drones. In: Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), pp. 548–555. SCITEPRESS, Lisbon (2015)
Cliff, D., Husbands, P., Harvey, I.: Evolving visually guided robots. In: Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB), pp. 374–383. MIT Press, Cambridge (1993)
D’Ambrosio, D.B., Stanley, K.O.: Scalable multiagent learning through indirect encoding of policy geometry. Evolutionary Intelligence 6(1), 1–26 (2013)
Dorigo, M., Trianni, V., Şahin, E., Groß, R., Labella, T., Baldassarre, G., Nolfi, S., Deneubourg, J., Mondada, F., Floreano, D., Gambardella, L.M.: Evolving self-organizing behaviors for a swarm-bot. Autonomous Robots 17(2), 223–245 (2004)
Duarte, M., Oliveira, S., Christensen, A.L.: Towards artificial evolution of complex behavior observed in insect colonies. In: Proceedings of the Portuguese Conference on Artificial Intelligence (EPIA), pp. 153–167. Springer, Berlin (2011)
Duarte, M., Silva, F., Rodrigues, T., Oliveira, S.M., Christensen, A.L.: JBotEvolver: a versatile simulation platform for evolutionary robotics. In: Proceedings of the International Conference on the Synthesis & Simulation of Living Systems (ALIFE), pp. 210–211. MIT Press, Cambridge (2014)
Ficici, S.G., Watson, R.A., Pollack, J.B.: Embodied evolution: a response to challenges in evolutionary robotics. In: Proceedings of the European Workshop on Learning Robots, pp. 14–22. Citeseer (1999)
Gomes, J., Mariano, P., Christensen, A.L.: Cooperative coevolution of partially heterogeneous multiagent systems. In: Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, pp. 297–305. International Foundation for Autonomous Agents and Multiagent Systems (2015)
Gomes, J., Urbano, P., Christensen, A.L.: Evolution of swarm robotics systems with novelty search. Swarm Intelligence 7(2–3), 115–144 (2013)
Gomez, F.J., Miikkulainen, R.: Transfer of neuroevolved controllers in unstable domains. In: Proceedings of Genetic and Evolutionary Computation Conference (GECCO), pp. 957–968. Springer, Berlin (2004)
Jakobi, N.: Evolutionary robotics and the radical envelope-of-noise hypothesis. Adaptive Behavior 6(2), 325–368 (1997)
Lehman, J., Risi, S., D’Ambrosio, D.B., Stanley, K.O.: Rewarding reactivity to evolve robust controllers without multiple trials or noise. In: Proceedings of the Thirteenth International Conference on Artificial Life (ALIFE), pp. 379–386. MIT Press, Cambridge (2012)
Miglino, O., Lund, H.H., Nolfi, S.: Evolving mobile robots in simulated and real environments. Artificial Life 2(4), 417–434 (1995)
Nitschke, G.S., Eiben, A.E., Schut, M.C.: Evolving team behaviors with specialization. Genetic Programming and Evolvable Machines 13(4), 493–536 (2012)
Paenke, I., Branke, J., Jin, Y.: Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation. IEEE Transactions on Evolutionary Computation 10(4), 405–420 (2006)
Potter, M.A., Meeden, L.A., Schultz, A.C.: Heterogeneity in the coevolved behaviors of mobile robots: the emergence of specialists. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 1337–1343. Citeseer (2001)
Quinn, M., Smith, L., Mayley, G., Husbands, P.: Evolving controllers for a homogeneous system of physical robots: structured cooperation with minimal sensors. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences 361(1811), 2321–2343 (2003)
Shang, B., Crowder, R., Zauner, K.P.: Simulation of hardware variations in swarm robots. In: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 4066–4071. IEEE Press, Piscataway (2013)
Silva, F., Urbano, P., Correia, L., Christensen, A.L.: odNEAT: An Algorithm for Decentralised Online Evolution of Robotic Controllers. Evolutionary Computation 23(3), 421–449 (2015)
Trianni, V., Nolfi, S., Dorigo, M.: Cooperative hole avoidance in a swarm-bot. Robotics and Autonomous Systems 54(2), 97–103 (2006)
Waibel, M., Keller, L., Floreano, D.: Genetic team composition and level of selection in the evolution of cooperation. IEEE Transactions on Evolutionary Computation 13(3), 648–660 (2009)
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Romano, P., Nunes, L., Christensen, A.L., Duarte, M., Oliveira, S.M. (2016). Genome Variations. In: Reis, L., Moreira, A., Lima, P., Montano, L., Muñoz-Martinez, V. (eds) Robot 2015: Second Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-319-27146-0_24
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