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The focus of the work in this paper is a systems-theoretic construction, analysis, and evaluation of a deterministic model of human decision making relative to experimental data. In sequential two-alternative forced choice decision tasks, a human subject is presented with two choices at every time step, is given finite time to select one of the choices, and receives a reward after a choice is made (presented as a number on a computer screen). The goal for the human is to obtain the maximal reward while not knowing the underlying reward assignment process. In this work, we present a parameterized deterministic model for human decision making in this context and analyze optimality and stability using a finite state machine approach. This model is then evaluated relative to experimental data from human subjects performing each of six tasks.