When computers expressed their abilities for calculating and data processing, many scientists reached to the conclusion that, these machines can imitate the human mind, and they devoted their efforts to improve computers for achieving the human mind Artificially. Behind this effort, there is a fundamental philosophical attitude. To revise this approach, I will argue in this paper that: 1) modern philosophy and the most important notion of it, cogito, are foundations of this project which is named Artificial intelligence; and 2) I will show that, based on a Foucaultian vision, the hyperbolic version of Artificial intelligence is impossible.

The problem of assigning locomotives to trains consists of determining the number of locomotives of different types that provide sufficient power to pull trains on fixed schedules. The objective is to minimize the fixed and operational locomotive costs. The locomotive assignment problem is defined for cyclic and non cyclic problems. In this paper, an approach using a genetic algorithm and a neural network algorithm is presented to find a cyclic solution on a one-week horizon, while satisfying the power demands of all trains. This system was tested using realistic data from the Canadian National (C.N.) North America Company with about 1600 trains and 1300 locomotives.