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In this thesis, an approach is developed to obtain an optimal pricing policy for chartered flights. In order to do so, a model within the framework of dynamic programming is presented and its main structure is also analyzed. Since in real world cases the dimension of this model happens to be very large, a solution method is developed by “Q Learning” technique. This is an appropriate approach in approximate dynamic programming and reinforcement learning. Analysis is carried out under two different assumptions regarding demand, namely “linear-deterministic” and probabilistic demand for transition probabilities. An exact solution for deterministic demand case is developed. Furthermore, for...