IJARCCE - Computer and Communication Engineering

Abstract

Towers of Hanoi is a standard planning problem in the field of computer science. It has applications in various fields of engineering. Solution to Towers of Hanoi is generally provided by method of recursion. Recursion is a functional programming concept widely used to solve variety of problems. Recursion has been providing solution to this problem most efficiently; hence other methods of solving have not been explored. In this paper we study artificial intelligence method of solving the problem. Artificial intelligence is a field of study which aims at creating intelligence in computer systems. Genetic algorithm is a well-known algorithm for optimization used in artificial intelligence. In this paper we have studied a method of solving Towers of Hanoi using genetic algorithm. Parallelism is achieved through OpenMp.We propose a comparative study of both Genetic algorithm and Recursive algorithm in solving Towers of Hanoi puzzle. Results for the same are presented. I. INTRODUCTION Artificial intelligence is an emerging field of study. If implemented efficiently, it is a field with potential to change the world. It is a dream of every engineer to build system which is intelligent. In this paper we study a method based on artificial intelligence in solving Towers of Hanoi (1). The reason for study of this method is because it is a method which solves the problem without being explicitly programmed. Towers of Hanoi are a standard recursive problem in the field of computer science. It is well known mathematical puzzle invented by Edouard Lucas (hence also known as Lucas' Tower). The problem basically consists of three rods A, B and C. A known number of disks of unequal sizes are placed in one of the three rod (consider rod A). The problem is complete when all the disks are moved from one rod (rod A) to another rod (rod B) by making use of an auxiliary rod (rod B).The constraints for transfer of disks has following constraints.  Only one disk can be moved at a time.