Q-Learning Elicited Disaster Management System Using Intelligent Mapping Approach

Abstract

Artificial Intelligence (AI) is one of the thought provoking areas of exploration within the research community. In this area, reinforcement learning and computer vision techniques are coming under the focus. Research in AI focuses on the development and analysis of algorithms that perform intelligent behavior with minimal human intervention. Moreover, from several literatures it has been observed that enormous investigations have also been performed in robotics. In this paper, initially an attempt has been made to design an intelligent system triggered by improved Q-learning algorithm which can map in any unknown disaster environments and perform in a proficient fashion. Thereafter, the concept of robotics has been amalgamated to test the enhanced performance of the proposed system in real time. Thereafter, the performance of the proposed system has also been studied under different environments like constrained and unconstrained.