Intellectual Management - Cognitive Approach

Abstract

Control of structurally complex industrial and technological objects belongs to the class of problems of intelligent control, which demands making decisions in states of uncertainty. Further development of this industry will be associated with technologies of intelligent control based on knowledge. Such technologies use methods, models, and algorithms extracting and accumulating knowledge needed to find optimal decisions. Intelligent control theory is based on learning surrounding world and adapting to changes in the process of reaching the defined goal. In this paper we consider a cognitive approach to learning developed following the human cognitive ability and a scientific method of physics. Cognitive approach opens new wide directions towards control of industrial objects and situations that are not well structured and difficult to formalize, especially in real life circumstances with significant uncertainty. A class of cognitive models control agents based on the principles of learning is described in the paper. Cognitive agents are such kind of agents that are learning from their surrounding and modifying their actions to achieve the goals, this type of agents enables solving problems of a wide area of control in presence of uncertainty.