2012 IEEE Conference on Computational Intelligence and Games (CIG)最新文献_第6页

Monte Carlo Tree Search with macro-actions and heuristic route planning for the Physical Travelling Salesman Problem 物理旅行商问题的宏行为蒙特卡罗树搜索和启发式路径规划

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374161

E. Powley, D. Whitehouse, P. Cowling

引用次数: 39

From competition to cooperation: Co-evolution in a rewards continuum 从竞争到合作:奖励连续体中的共同进化

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374135

D. Ashlock, W. Ashlock, Spyridon Samothrakis, S. Lucas, Colin Lee

{"title":"From competition to cooperation: Co-evolution in a rewards continuum","authors":"D. Ashlock, W. Ashlock, Spyridon Samothrakis, S. Lucas, Colin Lee","doi":"10.1109/CIG.2012.6374135","DOIUrl":"https://doi.org/10.1109/CIG.2012.6374135","url":null,"abstract":"In this study the hypothesis that zero-sum (i.e strictly competitive) games are more difficult targets for co-evolution than non-zero-sum (i.e. games that are not strictly competitive nor strictly cooperative) games is examined. Our method is to compare the co-evolutionary behavior of a three move zero-sum game (rock paper scissors) with that of a three move non-zero-sum game (coordination prisoner's dilemma) as well as with intermediate games obtained using weighted averages of the games's payoff matrices. The games are compared by examining the way use of moves evolves, by using transitivity measures on evolved agents, by estimating the complexity of the agents and by checking for non-local adaptation. Two different agent representations, finite state machines with 8 and 64 states, are used. Unexpectedly, these two representations are found to have large, qualitative differences. The results support the hypothesis that co-evolving good strategies for zero-sum games is more difficult than for non-zero-sum games. Many of the measurements used to compare different games are found to exhibit a nonlinear responses to the change in payoff matrix.","PeriodicalId":288052,"journal":{"name":"2012 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131727858","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: 17

A procedural procedural level generator generator 程序程序关卡生成器

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374174

Manuel Kerssemakers, J. Tuxen, J. Togelius, Georgios N. Yannakakis

引用次数: 45

Learning and evolving combat game controllers 学习和发展战斗游戏控制器

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374156

Luis Peña, Sascha Ossowski, J. Sánchez, S. Lucas

引用次数: 18

Controlling cooperative and conflicting continuous actions with a Gene Regulatory Network 用基因调控网络控制合作与冲突的连续行为

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374155

Sylvain Cussat-Blanc, Stéphane Sanchez, Y. Duthen

引用次数: 13

Win/loss States: An efficient model of success rates for simulation-based functions 输赢状态:基于模拟功能的成功率的有效模型

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374136

Jacques Basaldua, J. M. Moreno-Vega

引用次数: 2

TD(λ) and Q-learning based Ludo players 基于TD(λ)和Q-learning的Ludo播放器

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-09-01 DOI: 10.1109/CIG.2012.6374142

Majed Alhajry, Faisal Alvi, Moataz A. Ahmed

引用次数: 7

Noise tolerance for real-time evolutionary learning of cooperative predator-prey strategies 协同捕食策略实时进化学习的噪声容忍

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-01-30 DOI: 10.1109/CIG.2012.6374134

M. Wittkamp, L. Barone, P. Hingston, Lyndon While

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引用次数: 3