The article analyzes the requirements for increasing the probability of conformity assessment of products. To increase the probability of measuring inspection, there have to be applied more precise measuring systems; performed multiple observations of the investigated quantity. An analysis was conducted for each of the ways.
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.