Learning and memory processes in autonomous agents using an intelligent system of decision-making

Abstract

This paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes ismodelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model of human memory (using, in particular, the concept of Long-Term Memory) are discussed. Finally, the paper presents a way of rearranging the system memory and modelling the processes of learning.