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Browsing Fen Bilimleri Enstitüsü by Subject "Game theory."

Browsing Fen Bilimleri Enstitüsü by Subject "Game theory."

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  • Akca, Sema Şengül. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2011., 2011.)
    The bilevel partial interdiction problem with capacitated facilities and demand outsourcing involves a static Stackelberg game between a system planner and a potential attacker. The system planner (defender) is responsible ...
  • Fas, Genco. (Thesis (Ph.D.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2012., 2012.)
    This work deals with the equilibrium strategies for substitutable product inventory control systems between two retailers in a nite horizon, two and single period cases. We investigate how a dynamic game framework can be ...
  • Kazanç, Mehmet Emin. (Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2018., 2018.)
    In this study, the correlations between EEG sources in multiple brain areas and the performance feedback in a motivation game were studied. EEG data were collected from 14 (6 male, 8 female) participants with 19 channels ...
  • Çavlı, Can. (Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2007., 2007.)
    Understanding cellular signaling is central for gaining insight into the molecular mechanisms behind diseases as well as adaptation of living cells to changes in the environment. Signaling pathways are often branched in ...
  • Derici, Rüştü. (Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2009., 2009.)
    The thesis analyses the dynamics of merger in three agent games. The purpose of the study is to nd out how merger a ects the social structure. To begin with the de nition of a game, it is a series of competitions. In these ...
  • Emekligil, Erdem. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2018., 2018.)
    Deep Reinforcement Learning (DRL) combines deep neural networks with re inforcement learning. These methods, unlike their predecessors, learn end-to-end by extracting high-dimensional representations from raw sensory data ...
  • Eksin, İbrahim. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 1979., 1979.)
    In designing control systems with optjmal performance parameter variations pose a great problem. In prjnciple, it is possible to attain an ideal performance by sensing the uncertain parameters and using an adaptive controller. ...
  • Alpar, Orcan. (Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2005., 2005.)

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