The logical type of Artificial Intelligence is presented in the article. MIVAR (Multidimensional Informational Variable Adaptive Reality) technology is based on the gnoseological triplet concept "Thing-Property-Relationship." The unlimited number of MIVAR units fill the MIVAR space that makes it communicatory, discrete, and scalable. MIVAR information processing allows creating complicated algorithms for medicine. We have chosen the clinical model of pain in the heart for preparation ontology for doctors. Knowledge expert model MIVAR WiMi "Chest Pain" is shown. The logical Artificial Intelligence (expert model) can help doctors fast, precisely and in the best way in the decision-making process. Except medical ontology Artificial Intelligence must have an empathic, emotional experience, without that medical care cannot be imagined. MIVAR technology is the closest to human thinking among other Artificial Intelligence technologies; it differs from the Artificial network of Mirror neurons, related to emotional perception, but MIVAR space with rules and constraints can imitate emotions and empathy.

The main field of our research is artificial intelligence already implemented in the experimental autonomous road vehicle. Artificial intelligence now is a really huge area of studies. This investigation is focused more on a development of intelligent systems. Such as expert systems, semantic text processing systems, semantic image understanding systems, robotics systems. Wi!Mi is a solution for developing mivar knowledge models. This tool belongs to the class of so-called ES shells - programs that allow significantly simplify and accelerate the ES development process. It uses a novel knowledge representation mechanism based on bipartite graphs and the significantly improved but simple inference engine, which is able to process large systems involving millions of variables in just a few seconds. A special representation model which is called mivar nets with linear computational complexity using if-then rules is used in Wi!Mi. The idea is that the subject domain is divided into objects and connections between them. Scientific investigation allows to implement new decision-making system called “RoboRazum” as a form of an embedded software platform with flexible capabilities to adapt to control by any robotic suites and systems. RoboRazum is a platform for designing autonomous robotic control systems. Provided solutions don’t require powerful computational resources and could be used in small systems-on-chip like microcontrollers. That is why this solution is perfectly fit with conception of Internet of Things (IoT). Reasoned and fast logical decisions based on mivar technologies play important role for autonomous road vehicles.

The task of creating a logical “strong” artificial intelligence (AI) to be used as new decision-making systems for autonomous vehicles, tractors, and robotic systems draws increasing attention of scientists around the world. Essentially, it is the creation of “brains” for vehicles and any other transport systems, including cyber-physical systems. The mivar technologies of logical AI allowed solving many problems at a qualitatively new level and reducing the decision-making time from billions of years to hundredths of seconds, which enables real-time vehicle control. This paper shows how the application of mivar products (mivar expert systems) allows solving another class of problems – state-space planning (STRIPS planning). In turn, the solutions of these problems enable the development of driver assistance systems at a new level and creation of a fully autonomous vehicle.

To control machines and robots, in addition to the well-known reflex level control systems, it is proposed to use logical level decision-making systems that are created on the basis of mivar expert systems. It is shown that the use of mivar expert systems makes it possible to solve problems of automatic planning of actions of robots in the state space. These tasks relate to STRIPS planning. The results of the study of the Mivar-based Intelligent Planner of Robot Actions (MIPRA) project have dramatically reduced the computing infrastructure requirements from servers to conventional computers and the time it takes to plan tasks for robot activities from weeks to seconds. Similar results after creating special knowledge bases can be obtained for groups of robots, multi-level heterogeneous robotic systems and cyber-physical systems of various bases and purposes, which is an important section in the control of machines and robots. Solving automatic planning tasks makes it possible to quickly develop driver assistance systems and move on to creating a fully autonomous smart car.

The paper deals with the process of designing question-answering system "Mivar Virtual Consultant" using specialized information-technology platform for understanding meaning of text in the natural Russian language. The system is capable of accumulating knowledge from texts in the natural Russian language and managing this knowledge. The methodology for training virtual consultant is described.