Open AccessFUZZY LINEAR PROGRAMMING PROBLEMS IN MOTIVATED SYSTEMS
Author(s) -
Gennady Vinogradov,
В. Д. Кузнецов,
В.Н. Богатиков
Publication year - 2019
Publication title -
vestnik astrahanskogo gosudarstvennogo tehničeskogo universiteta. seriâ: upravlenie, vyčislitelʹnaâ tehnika i informatika
Language(s) - English
Resource type - Journals
eISSN - 2224-9761
pISSN - 2072-9502
DOI - 10.24143/2072-9502-2019-4-131-140
Subject(s) - action (physics) , computer science , representation (politics) , perception , artificial intelligence , fuzzy logic , state (computer science) , basis (linear algebra) , action selection , selection (genetic algorithm) , psychology , mathematics , algorithm , physics , geometry , quantum mechanics , neuroscience , politics , political science , law
The paper presents an approach to solving the problem of agent selection model, where the agent endogenously forms the goals of its behavior. The approach involves the development of decision-making methods, taking into account the relationship of motivation with the desire of the agent to implement subjectively understood interests and the state of the environment. The environment exists only in the mind of the agent in the form of a symbolic model based on the information perceived from the sensors. It serves as a basis for the agent's understanding of the current situation and subsequent choice of the method of action. Desire of the agent to strengthen the confidence in feasibility of the method of action and possibility of achieving the desired state requires to use the procedures for forming a model-representation based on the measured values of the state of the environment. There are considered the cases of applying the methods of the possibility theory for modeling reality with an artificial or natural entity based on the perception of facts, existing knowledge, memory, judgments and hypotheses.