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SUMMARYNetwork selection mechanisms have a significant role in guaranteeing the QoS for users in a heterogeneous wireless networks environment. These mechanisms allow the selection of an optimal wireless network to satisfy the needs of users. Users are provided with the opportunity to select from multiple connectivity opportunities available all over various wireless networks. Furthermore, the network operators themselves can execute active selection strategies that facilitate proper decision making, in which user preferences are considered. This study proposes a new noncooperative competing game-theoretic model and strategy space based on user preference. This model can solve network selection problems and capture the inter-linkages of decisions taken by various networks. A generalized simple additive weighting method is incorporated into the framework of noncooperative game theory. In addition, the utility function is employed to assess the usefulness of the system. Simulation results and analysis illustrate the efficacy of the suggested model in attaining optimum network utility for heterogeneous wireless networks while optimizing user satisfaction.

In this article, we demonstrate the use of composing 'experience' in the form of piece location probability values derived from a database of matein-3 chess problems. This approach was compared against a 'random' one. Comparisons were made using 'experiences' derived from three different databases, i.e. problems by human composers (HC), computer-generated compositions that used the HC experience (CG), and mating 'combinations' taken from tournament games between humans (TG). Each showed a reasonable and statistically significant increase in efficiency compared to the random one but not each other. Aesthetically, the HC and CG were better than the others. The results suggest that composing efficiency and quality can be improved using simple probability information derived from human compositions, and unexpectedly even from the computer-generated compositions that result. Additionally, these improvements come at a very low computational cost. They can be used to further aid and entertain human players and composers.