Modification of Game Agent using Genetic Algorithm in Card Battle game

Author:

Phillip N A,Permana S D H,Cendana M

Abstract

Abstract Game Agent is currently being developed to be an opponent in the game, including games with the Card Games genre. Game Agents on traditional Card Games - such as poker, dominoes, or mahjong cards - have abilities that depend on the value of the cards, but the ability of these Game Agents will not be optimal if used in the Card Battle game. This is because Card Battle has many attributes that must be processed to become opponents. Therefore, this research modifies the Game Agent with Genetic Algorithm to optimize the playing ability of the Game Agent in Card Battle. The computational stages and fitness formula of the Genetic Algorithm are adjusted to the Card Battle rules to increase the computational speed of the Genetic Algorithm. The results of this study prove that Game Agent modification of Genetic Algorithm provides a more optimal playing ability than its predecessor algorithm. Game Agent that has been modified has several abilities that are not owned by the previous Game Agent, such as issuing cards to attack opponents directly and storing SP (Summon Points) they have.

Publisher

IOP Publishing

Subject

General Medicine

Reference10 articles.

1. Learning via game design: From digital to card games and back again;Marchetti;Electron. J. e-Learning,2015

2. Monsters of Darwin: A strategic game based on artificial intelligence and genetic algorithms;Norton;CEUR Workshop Proc.,2017

3. Implementation of Min Max Algorithm as Intelligent Agent on Card Battle Game;Permana;IJISTECH (International Journal of Information System & Technology),2019

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A literature review of genetic algorithm applied to games;Journal of Computational Methods in Sciences and Engineering;2023-02-04

2. Battle Card, Card Game for Teaching the History of the Incas Through Intelligent Techniques;Lecture Notes in Networks and Systems;2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3