Modeling and designing of machine learning procedures as applied to game playing using artificial intelligence

• Authors: Avneet Kaur Dhawan;Jaswinder Singh
• Venue: ACAI '11 Proceedings of the International Conference on Advances in Computing and Artificial Intelligence
• Year: 2011

In this paper, we are proposing a method which is different from many practical computer programs have been developed to exhibit useful types of learning. For problems such as speech recognition, different algorithms based on machine learning outperform all other approaches that have been attempted to date. In the field known as data mining, machine learning algorithms are being used commonly to discover valuable knowledge from large commercial databases containing equipment maintenance records, loan applications, financial transactions, medical records etc. Thus, it seems inevitable that machine learning will play an integral role in computer science and computer technology. In this paper, modeling and designing of a general learning system is proposed that presents new machine learning procedures used to arrive at "knowledgeable" static evaluators for checker board positions. The static evaluators are compared with each other, and with the linear polynomial using two different numerical indices reflecting the extent to which they agree with the choices of checker experts in the course of tabulated book games. The new static evaluators are found to perform about equally well, despite the relative simplicity of the second; and they perform noticeably better than the linear polynomial.