A seller in a free competitive market attempts to optimize his profit by manipulating the price of his commodity. A seller does not know a priori the market conditions such as the conditional probability of the buyers demand, the criteria or even the number of his seller opponents. Subject to this lack of information, the process of market price formation can be simulated as a game between stochastic automata. As time unfolds each seller-automaton learns the market conditions and changes accordingly its price probabilities in view of maximizing its profit. A simple reinforcement scheme is introduced for the design of such automata. The simulation results demonstrate the expediency of the automata behavior.

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