The neuroagent model of decision-making in the conditions of uncertainty is investigated. Adaptive methods of an artificial neural network learning without the teacher are considered. The algorithm and program model of neuroagent decision-making are developed. Efficiency of neuroagent decision-making has been confirmed by results of computer experiment. Influences of parameters of model on the neuroagent learning rate are investigated.