Immune robustness from top to down: bio-inspired immune- based behavior coordination for autonomous mobile robot navigation
Abstract
Behavioral robustness at antibody and immune network levels is discussed. The robustness of the immune response that drives an autonomous mobile robot is examined with computational experiments in the trajectory generation context in unknown environments. The immune response is met based on the immune network metaphor for different low-level behaviors coordination. These behaviors are activated when a robot sense the appropriate conditions in the environment in relation to the network current state. Results are obtained over case studies in computer simulation as well as in laboratory experiments with a Khepera II microrobot, and also when such an immune response is externally perturbed at network or low-level behavioral modules for behavioral robustness. Results indicate that robust behavior and immune responses relate to the coupling between behavioral modules that are selectively engaged with the environment based on immune response. The importance of results is that such a demonstration, because of the simplicity, leads discussions on a dynamical systems perspective of behavioral robustness in artiicial immune systems that goes beyond the isolated immune network response, but the antibody self-response with implications on bio-inspired systems research. Challenges and limitations of the proposed approach are also identiied for future studies.
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Acosta, G.G., Curti, H., Calvo Ibáñez, O., & Rossi, S. (2009). Some Issues on the Design of a Low-Cost Autonomous Underwater Vehicle with an Intelligent Dynamic Mission Planner for Pipeline and Cable Tracking, Chapter I in Underwater Vehicles, I-Tech Online Books, Robotics Series, I-Tech Education and Publishing KG, Viena, Austria, Editor: A. Inzartsev (pp. 1-18).
Alon, U. (2006). An Introduction to Systems Biology: Design Principles of Biological Circuits. Mathematical & Computational Biology. Chapman & Hall.
Arbib, M. (Ed.) (1995). The Handbook of Brain Theory and Neural Networks. The MIT Press.
Calabretta, R., Noli, S., Parisi, D., & Wagner, G. (1998). Emergence of functional modularity in robots. In From Animals to Animats, (ed. R. Pfeifer B. Blumberg J.-A. Meyer and S. W. Wilson), 497-504. Cambridge, Mass.
Dasgupta. D. (Ed.) (1999). Artiicial immune Systems and their Applications. Springer-Verlag.
de Castro, L.N., & Timmis, J.I. (2002). Artiicial Immune Systems: A New Computational Intelligence Approach, Springer-Verlag.
Farmer. J.D., Packard. N.H., & Perelson, A.S. (1986). The Immune System. Adaptation and Machine Learning, Physica 22D (pp. 187-204).
Fernandez-Leon, J.A. (2006). Study of Evolutionary Neurocontrollers for Autonomous Robot Navigation. Master Thesis in Systems Engineering. UNCPBA, Argentina. (In Spanish).
Fernandez-Leon, J.A. (2009). Bio-Inspired Immune-Based Behaviour Coordination for Autonomous Mobile Robot Navigation. Doctoral Thesis, UNCPBA, Argentina.
Fernandez-Leon, J.A., & Di Paolo, E. (2007). Neural Uncertainty and Sensorimotor Robustness. Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey,
I. and Coutinho, A., editors, Advances in Artiicial Life. Proceedings of the 9th European Conference on Artiicial life ECAL 2007 (pp. 786-795). Berlin/ Heidelberg: Springer.
Fernandez-Leon, J.A., & Di Paolo, E. (2008). Neural noise induces the evolution of robust behaviour by avoiding non-functional bifurcations. Asada, M., Hallam, J.C.T., Meyer, J.-A. and Tani, J., editors, From Animals to Animats 10. 10th International Conference on the Simulation of Adaptive Behavior (pp. 32-41). Springer.
Fernandez-Leon, J.A., Acosta, G., & Mayosky, M. (2009). Behavioral control through evolutionary neurocontrollers for autonomous mobile robot navigation. Journal of Robotics & Autonomous Systems, Elsevier, Vol. 57, pp. 411 – 419.
Fernandez-Leon, J.A., Acosta, G., Mayosky, M., & Calvo Ibáñez, O. (2009). A Biologically Inspired Control based on Behavioural Coordination in Evolutionary Robotics, Chapter VII in Advancing Artiicial Intelligence through Biological Process Applications , pp. 107-129, IGI-Global (Idea Group Inc.), USA-UK. Editors: Dr. A. B. Porto, Dr. A. Pazos, and Dr. W. Buño, 2009. (ISBN: 978-1- 59904-996-0).
Ishiguro, A., Kondo. T., Watanabe, Y. Shirai, Y., & Uchikawa, H. (1996). Immunoid: A Robot with a Decentralized Consensus-Making Mechanism Based on the Immune System. Presented at ICMAS Workshop on Immunity-Based Systems, December (pp. 82-92).
Kitano, H. (2004). Biological Robustness. Nature Reviews: Genetics 5, Nature Publishing Group, 826-837.
Kitano, H. (2006). Robustness from top to bottom. Book review of Wagner (2005): Robustness and Evolvability in Living Systems. Nature Genetics 38, 133.
Kitano, H. (2007). Towards a theory of biological robustness. Molecular Systems Biology 3:137. EMBO and Nature Publishing Group.
Michelan, R., & Von Zuben, F.J. (2002). Decentralized Control System for Autonomous Navigation based on an Evolved Artiicial Immune Network. Proc. of the 2002 Congress on Evolutional. Computation (CEC‘2002). YOI. 2. (pp. 1021-1026).
Nolfi, S. & Floreano. D. (2000). Evolutionary Robotics: The Biology. Intelligence and Tech. of Self-Organizing Machines. The MIT Press.
Stelling, J., Sauer, U., Szallasi, Z., Doyle III, F., & Doyle, J. (2004). Robustness of cellular functions. Cell 118, 675–685.
Vargas, P. A., de Castro, L.N., Michelan, R., & Von Zuben, F.J. (2003). Implementation of an Immuno-Genetic Network on a Real Khepera II Robot. Proc. of the Congress on Evolutionary Computation-CEC-2003, Special Session on Artiicial Immune Systems, held in Canberra, Australia, December 8-12, 2003 (pp. 420-426).
Wang, L., Wang, L., & Nie, Y. (2006). A Novel Artiicial Immune Network Model and Analysis on Its Dynamic Behavior and Stabilities. In Proceedings of ICNC (2)’2006 (pp.83-91).
Whitbrook, A. (2005) An Idiotypic Immune Network for Mobile Robot Control. M.Sc. in Management of IT thesis, Univ. of Nottingham, UK.
Whitbrook, A., Aickelin, U., & Garibaldi, J. (2007). Idiotypic Immune Networks in Mobile-Robot Control, IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, Vol.37, No. 6 (pp 1581-1598).
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