12th World Conference on Intelligent Systems for Industrial Automation, WCIS 2022, Tashkent, Uzbekistan, 25 - 26 November 2022, vol.718 LNNS, pp.352-360
Real-world decision-making problems are characterized by a fusion of fuzzy and probabilistic uncertainties. In view of this, Zadeh introduced the concept of Z-number to describe imprecision and partial reliability of decision relevant information. In this paper we proposed an approach to solving Q-learning problem where rewards and constraints over actions are described by using Z-numbers. A typical decision problem is used to illustrate the approach.