2015 IEEE Conference on Computational Intelligence and Games (CIG)最新文献_第3页

A data-driven approach for online adaptation of game difficulty 一种数据驱动的在线游戏难度调整方法

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317918

Haiyan Yin, Linbo Luo, Wentong Cai, Y. Ong, J. Zhong

引用次数: 12

Investigating MCTS modifications in general video game playing 调查MCTS在一般电子游戏中的修改

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317937

F. Frydenberg, Kasper R. Andersen, S. Risi, J. Togelius

引用次数: 32

Evolvable fashion-based cellular automata for generating cavern systems 用于生成洞穴系统的基于进化时尚的元胞自动机

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317958

D. Ashlock

引用次数: 17

Convergence and correctness analysis of Monte-Carlo tree search algorithms: A case study of 2 by 4 Chinese dark chess 蒙特卡罗树搜索算法的收敛性及正确性分析——以2 × 4中国黑棋为例

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317963

Hung-Jui Chang, Chih-wen Hsueh, T. Hsu

{"title":"Convergence and correctness analysis of Monte-Carlo tree search algorithms: A case study of 2 by 4 Chinese dark chess","authors":"Hung-Jui Chang, Chih-wen Hsueh, T. Hsu","doi":"10.1109/CIG.2015.7317963","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317963","url":null,"abstract":"The convergence and correctness of the UCT algorithm is a hot research problem. Previous research has shown the convergence of UCT-based algorithm on simultaneous turns or random turns games, but little is known for traditional alternating turns games. In this paper, we analyze the performance of the UCT algorithm in a 2-player imperfect information alternating turns game, 2 × 4 Chinese dark chess (CDC). The performance of the UCT algorithm is measured by the correctness rate and convergence speed. The correctness is defined by the percentage that the UCT algorithm outputs the same move with the one having the best game theoretic value. The convergence speed is defined by the entropy of a set of moves, which are output by the UCT algorithm using the same number of iterations. Experimental result shows the convergence of the UCT algorithm in the CDC, which can also be applied to explain the existence of diminishing returns in the UCT algorithm. Experimental result also shows an UCT algorithm does not always output moves with the best game theoretic value, but these with the highest chance of winning.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122173118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Evolving strategies to help resolve tragedy of the commons social dilemmas 不断发展的策略，以帮助解决悲剧的公地社会困境

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317905

G. Greenwood

引用次数: 2

Automatic mapping of human behavior data to personality model parameters for traffic simulations in virtual environments 虚拟环境交通仿真中人类行为数据到人格模型参数的自动映射

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317925

Steffen Kampmann, Sven Seele, R. Herpers, Peter Becker, C. Bauckhage

引用次数: 5

Systems for player reputation with NPC agents 玩家与NPC代理人的声誉系统

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317670

J. A. Brown, Qiang Qu

引用次数: 4

Towards generating arcade game rules with VGDL 用VGDL生成街机游戏规则

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317941

Thorbjørn S. Nielsen, Gabriella A. B. Barros, J. Togelius, M. Nelson

{"title":"Towards generating arcade game rules with VGDL","authors":"Thorbjørn S. Nielsen, Gabriella A. B. Barros, J. Togelius, M. Nelson","doi":"10.1109/CIG.2015.7317941","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317941","url":null,"abstract":"We describe an attempt to generate complete arcade games using the Video Game Description Language (VGDL) and the General Video Game Playing environment (GVG-AI). Games are generated by an evolutionary algorithm working on genotypes represented as VGDL descriptions. In order to direct evolution towards good games, we need an evaluation function that accurately estimates game quality. The evaluation function used here is based on the differential performance of several game-playing algorithms, or Relative Algorithm Performance Profiles (RAPP): it is assumed that good games allow good players to play better than bad players. For the purpose of such evaluations, we introduce two new game tree search algorithms, DeepSearch and Explorer; these perform very well on benchmark games and constitute a substantial subsidiary contribution of the paper. In the end, the attempt to generate arcade games is only partially successful, as some of the games have interesting design features but are barely playable as generated. An analysis of these shortcomings yields several suggestions to guide future attempts at arcade game generation.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129764511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 48

Tutorial I: Video Game Description Language (VGDL) and the challenge of creating agents for General Video Game Playing (GVGP) 教程1:电子游戏描述语言(VGDL)和为通用电子游戏玩法(GVGP)创建代理的挑战

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317661

Diego Perez

{"title":"Tutorial I: Video Game Description Language (VGDL) and the challenge of creating agents for General Video Game Playing (GVGP)","authors":"Diego Perez","doi":"10.1109/CIG.2015.7317661","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317661","url":null,"abstract":"Games have attracted many AI researchers over the last decades, allowing to benchmark multiple and varied simulated environments to test AI algorithms in. It is not rare that information about the game played is supplied in order to help the algorithm to achieve better results. This may pose a problem: in some cases it is debatable if the success of a given technique is due to the algorithm itself or to the heuristics employed. In the worse case scenario, one could argue that the research outcome is of little interest to AI because it is too tailored to the game used. General Game Playing (GGP; for board games) and General Video Game Playing (GVGP; for real-time games) are disciplines that try to tackle this issue by employing several games, that must be played by the same algorithm. The number and types of heuristics that can be used is limited by the nature of the problem: domain-specific knowledge can overspecialize the algorithm to one or some of the games, which becomes a problem if some of them are not known in advance. In this tutorial, we will explore the Video Game Description Language (VGDL) and the challenge of creating agents for GVGP. We will use the General Video Game AI (GVGAI) framework, employed for the GVGAI competition, to create different types of controllers, from simple to more complex solutions. These controllers will be able to play, at distinct performance levels, many different games without the need of domain specific heuristics. Furthermore, we will analyze the present and future challenges of GVGAI, as well as the different research opportunities it offers.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"61 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120810594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An experimental study of action selection mechanisms to create an entertaining opponent 创造有趣对手的行动选择机制的实验研究

2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-11-05 DOI: 10.1109/CIG.2015.7317939

Nick Sephton, P. Cowling, Nicholas H. Slaven

引用次数: 11