Large-scale strategic games and adversarial machine learning

@article{Alpcan2016LargescaleSG,
  title={Large-scale strategic games and adversarial machine learning},
  author={Tansu Alpcan and Benjamin I. P. Rubinstein and Christopher Leckie},
  journal={2016 IEEE 55th Conference on Decision and Control (CDC)},
  year={2016},
  pages={4420-4426}
}
  • Tansu Alpcan, Benjamin I. P. Rubinstein, Christopher Leckie
  • Published 2016
  • Computer Science, Mathematics
  • 2016 IEEE 55th Conference on Decision and Control (CDC)
  • 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… CONTINUE READING

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