Abstract
Altruism may be found in sets (groups of solutions). In such cases, it may occur that individual/individuals degrade their chances of survival (with sacrifice in the extreme) to ensure survival of fitter individuals. The idea of altruism within group evolution is posed here as a multi objective problem. The aspiration of a group to survive (find an optimal solution) is posed versus the individual’s aspiration to survive. In the paper, the problem is a trajectory planning problem with the dilemma producing a Pareto set for a decision maker to choose from. It is shown that if the decision maker is ready to forfeit some of the group members, optimality may be gained. Evolutionary multi objective algorithm is implemented in order to search for this optimal set.
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References
Hamilton, W.D.: The Genetical Evolution of Social Behavior I and II. Journal of Theoretical Biology 7, 1–16, 17–32 (1964)
Darwin, C.: The Descent of Man and Selection in Relation to Sex. Appleton, New York (1871)
West, S.A., Griffin, A.S., Gardner, A.: Social Semantics: Altruism, Cooperation, Mutualism, Strong Reciprocity and Group Selection. Journal of Evolutionary Biology 20, 415–432 (2007)
Lehmann, L., Keller, L., West, S., Roze, D.: Group Selection and Kin Selections: Two Concepts but One Process’. Proceedings of the National Academy of the Sciences 104(16), 6736–6739 (2007)
Sober, E.: Did Evolution Make us Psychological Egoists? In: His From A Biological Point of View. Cambridge University Press, Cambridge (1994)
Coello, C.A.C.: Recent Trends in Evolutionary Multiobjective Optimization. In: Ajith, A., Jain, L., Robert, G. (eds.) Evolutionary Multiobjective Optimization: Theoretical Advances and Applications, pp. 7–32. Springer, London (2005)
Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the strength Pareto evolutionary algorithm. Technical report 103, Computer Engineering and Networks Laberatory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, Gloriastrasse 35, CH-8092 Zurich, Switzerland (May 2001)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.A.: Fast and elitist multiobjective genetic algorithm. NSGA–II. IEEE Transactions on Evolutionary Computation 6(2), 182–197 (2002)
Deb, K.: Multi-objective optimization using evolutionary algorithms. J. Wiley & Sons, Ltd., Chicester (2001)
Saravanan, R., Ramabalan, S., Balamurugan, C.: Evolutionary multi-criteria trajectory modeling of industrial robots in the Presence of obstacles. Engineering Applications of Artificial Intelligence 22, 329–342 (2009)
Mittal, S., Deb, K.: Three-dimensional path planning for UAVs using multi-objective evolutionary algorithms. In: Proceedings of the Congress on Evolutionary Computation (CEC 2007), pp. 25–28 (September 2007)
Watanabe, K., Kiguchi, K., Izumi, K., Kunitake, Y.: Path planning for an omnidirectional mobile manipulator byevolutionary computation. In: Third International Conference Knowledge-Based Intelligent Information Engineering Systems, pp. 135–140 (1999)
Wei, J., Liu, J.: Collision free composite n3- splines generation for non-holonomic mobile robots by parallel variable length genetic algorithm. In: Int. Conference on Computational intelligence for Modeling control and Automation, CIMCA 2008, Vienna, Austria, December 10-12 (2008)
Lucidarme, P., Simonin, O., Liegeois, A.: Implementation and evaluation of a satisfaction/altruism based architecture for multi-robot systems. In: Proc. IEEE Int. Conf. on Robotics and Automation, pp. 1007–1012 (2002)
Simonin, O., Ferber, J.: Modeling self-satisfaction and altruism to handle action and reactive cooperation. In: SAB 2000 Proceedings, pp. 314–323 (2000)
Morton, R.D., Bekey, G.A., Clark, C.M.: Altruistic Task Allocation despite Unbalanced Relationships within Multi-Robot Communities. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, USA, October 11-15 (2009)
Schrum, J., Miikkulainen, R.: Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference, Stanford, California, October 22–24. AAAI Press, California (2008)
Floreano, D., Mitri, S., Perez-Uribe, A., Keller, L.: Evolution of Altruistic Robots. In: Zurada, J.M., Yen, G.G., Wang, J. (eds.) Computational Intelligence: Research Frontiers. LNCS, vol. 5050, pp. 232–248. Springer, Heidelberg (2008)
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Avigad, G., Eisenstadt, E., Weiss, M. (2010). The Optimization versus Survival Problem and Its Solution by an Evolutionary Multi Objective Algorithm. In: Deb, K., et al. Simulated Evolution and Learning. SEAL 2010. Lecture Notes in Computer Science, vol 6457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17298-4_53
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DOI: https://doi.org/10.1007/978-3-642-17298-4_53
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