By Ozgur Koray Sahingoz (auth.), Youn-Hee Han, Doo-Soon Park, Weijia Jia, Sang-Soo Yeo (eds.)
Recent advances in digital and desktop applied sciences have lead the way for the proliferation of ubiquitous computing and leading edge purposes that contain those applied sciences. This lawsuits e-book describes those new and cutting edge applied sciences, and covers themes like Ubiquitous conversation and Networks, safety platforms, clever units and functions, Cloud and Grid platforms, Service-oriented and net provider Computing, Embedded and snapshot Processing and Multimedia.
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Extra info for Ubiquitous Information Technologies and Applications: CUTE 2012
The idea of using coevolutionary algorithms to solve games was first proposed in a work by Amaral and Gomide in 2007. They used a coevolutionary approach to solve fuzzy games, but their proposed method only finds one sample Nash point for two person games and they do not consider the multi-modal optimization problem . 3 Problem Formulation Consider a finite n- person game in normal form. There is a set N ¼ f1; 2; . ; ng of players and for each player i 2 N a strategy set Si ¼ fsi1 ; si2 ; .
Math. 1, 73–79 (1971) 11. : Computing equilibria of N- person games. SIAM J. Appl. Math. 21, 80–87 (1971) 12. : An Introduction to Linear Programming and Game Theory. Wiley, New York (1988) 13. : An analysis of cooperative coevolutionary algorithms. PhD Thesis, George Mason University (2003) 14. : Computing Nash equilibria through computational intelligence methods. J. Comput. Appl. Math. 175, 113–136 (2005) 15. : An evolutionary model for solving multi-player non-cooperative games. In: Proceedings of the International Conference on Knowledge Engineering, pp.
The second factor of importance is the number of game players. For the games with two players, Nash equilibrium solves a system of linear equations over the variables in the support of the equilibrium. But the methods that work for two person games can not typically be directly extended for n-person games. The third factor that determines the choice of method concerns the type of Nash equilibria that we wish to find. It is well known that not all Nash equilibria are equally attractive. A large literature exists on equilibrium refinements, which defines criteria for selecting among multiple equilibria [2, 6].