Machine as one player in Indian Cowry board game: strategies and analysis of randomness model for playing

Nagabhushan, P. and Davoudian, Pouyan (2017) Machine as one player in Indian Cowry board game: strategies and analysis of randomness model for playing. International Journal on Recent and Innovation Trends in Computing and Communication, 5 (2). pp. 57-67. ISSN 2321-8169

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Abstract

Cowry game is an ancient board game originated in India. It is a game of chance and strategy with the objective of moving players� pieces through a specified path into a final location, according to the roll of special dice (cowry shells). This game involves decision-making under uncertainty and fuzziness with more than two parties; hence it can serve as an excellent example to apply methods and concepts for automating resource management and real-time strategic decisions. This research is aimed at evaluating the complexity of Cowry game and proposing heuristics and strategies that could be the basis of an adaptive artificial player to maximize its chances of winning the game. The main objective for considering machine as one player in Cowry game is to automate different strategies and to develop a machine player which is capable of real-time decision-making under interaction with live opponents. In this paper, we formulate several playing strategies and provide theoretical measures for comparison of these strategies. However, the main focus of this work is on analysis of playing randomly which involves no decision-making or intelligence. By applying this approach, we entirely concentrate on designing the game interface and validating the correctness of our implementation. Furthermore, the enhanced knowledge base resulting from analyzing the performance of the random strategy can be used for understanding the scenarios to be taken care of while evolving other types of strategies.

Item Type:	Article
Uncontrolled Keywords:	artificial intelligence; board game; cowry shell; game theory; machine learning; probability; race game; randomness; strategy
Subjects:	D Physical Science > Computer Science
Divisions:	Department of > Computer Science
Depositing User:	C Swapna Library Assistant
Date Deposited:	03 Jul 2019 06:19
Last Modified:	03 Jul 2019 06:19
URI:	http://eprints.uni-mysore.ac.in/id/eprint/4557

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