On one approach to measurement of robotic complexes autonomy and intelligence

With the development of artificial intelligence (AI), the problem of measuring the degree of robotic complexes autonomy has been arisen. Robotic complexes autonomy is determined by their control systems intelligence, i.e. the ability of robotic complexes to react and make decisions in various situations. The problem of measuring robotic complexes intelligence is related to the assessment of decision-making algorithms complexity. This problem is studied in the sphere of «expert systems» using the metric «variables, rule». This approach is based on estimating the maximum possible combinations numbers in a situation determined by the factorial of decision-making rules numbers. So the evaluation criterion is «the worst case of complexity» with a complete search of all possible rules describing the situation. These rules describe possible actions of robotic complexes in a certain situation, and all possible solutions are determined by the factorial depending from the number of rules ($N!$).