Conference Proceedings

Large-scale strategic games and adversarial machine learning

T Alpcan, BIP Rubinstein, C Leckie

2016 IEEE 55th Conference on Decision and Control (CDC) | IEEE | Published : 2016


Decision making in modern large-scale and complex systems such as communication networks, smart electricity grids, and cyber-physical systems motivate novel game-theoretic approaches. This paper investigates big strategic (non-cooperative) games where a finite number of individual players each have a large number of continuous decision variables and input data points. Such high-dimensional decision spaces and big data sets lead to computational challenges, relating to efforts in non-linear optimization scaling up to large systems of variables. In addition to these computational challenges, real-world players often have limited information about their preference parameters due to the prohibit..

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