2012 IEEE Conference on Computational Intelligence and Games (CIG)最新文献_第4页

Learning to intercept opponents in first person shooter games 学习在第一人称射击游戏中拦截对手

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374144

Bulent Tastan, Yuan Chang, G. Sukthankar

引用次数: 25

Deck-based prisoner's dilemma 基于甲板的囚徒困境

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374133

D. Ashlock, Elizabeth Knowles

{"title":"Deck-based prisoner's dilemma","authors":"D. Ashlock, Elizabeth Knowles","doi":"10.1109/CIG.2012.6374133","DOIUrl":"https://doi.org/10.1109/CIG.2012.6374133","url":null,"abstract":"A deck-based game is a modification of a game that normally permits the players to use any number of moves of any type. This freedom of choice of moves is limited by handing each player a deck of cards, each of which with a single move printed on it. The player must then play from their deck rather than simply choosing the moves. This study documents that deck-based iterated prisoner's dilemma is radically different from standard prisoner's dilemma when the entire deck must be expended during play. The restrictions imposed by the deck change the game into a coordination game or an anti-coordination game. The game is shown to transform smoothly into standard prisoner's dilemma as the fraction of the deck used in play is reduced, assuming that a constant ratio of the two types of moves are used in the deck. The size of the deck, ratio of defects to cooperates, and evolutionary algorithm parameters are all studied using a string based representation. An adaptive agent representation is also developed, based on augmented finite state machines called deck automata. Deck automata evolve to play the game more effectively than the string based agents for three different situations; experiments in which agents expend all, three-quarters, or half the available cards.","PeriodicalId":288052,"journal":{"name":"2012 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"20 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":"130043925","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: 8

Reactive control of Ms. Pac Man using information retrieval based on Genetic Programming 基于遗传规划信息检索的吃豆女士反应控制

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374163

Matthias F. Brandstetter, S. Ahmadi

{"title":"Reactive control of Ms. Pac Man using information retrieval based on Genetic Programming","authors":"Matthias F. Brandstetter, S. Ahmadi","doi":"10.1109/CIG.2012.6374163","DOIUrl":"https://doi.org/10.1109/CIG.2012.6374163","url":null,"abstract":"During the last years the well-known Ms. Pac Man video game has been - and still is - an interesting test bed for the research on various concepts from the broad area of Artificial Intelligence (AI). Among these concepts is the use of Genetic Programming (GP) to control the game from a human player's perspective. Several GP-based approaches have been examined so far, where traditionally they define two types of GP terminals: one type for information retrieval, the second type for issuing actions (commands) to the game world. However, by using these action terminals the controller has to manage actions issued to the game during their runtime and to monitor their outcome. In order to avoid the need for active task management this paper presents a novel approach for the design of a GP-based Ms. Pac Man controller: the proposed approach solely relies on information retrieval terminals in order to rate all possible directions of movement at every time step during a running game. Based on these rating values the controller can move the agent through the mazes of the the game world of Ms. Pac Man. With this design, which forms the main contribution of our work, we decrease the overall GP solution complexity by removing all action control management tasks from the system. It is demonstrated that by following the proposed approach such a system can successfully control an autonomous agent in a computer game environment on the level of an amateur human player.","PeriodicalId":288052,"journal":{"name":"2012 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"32 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":"121031728","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: 23

Comparison of Bayesian move prediction systems for Computer Go 计算机围棋贝叶斯走法预测系统的比较

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374143

Martin Wistuba, L. Schaefers, M. Platzner

引用次数: 17

BeatTheBeat music-based procedural content generation in a mobile game 基于BeatTheBeat音乐的手机游戏程序内容生成

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374172

Annika Jordan, Dimitri Scheftelowitsch, Jan Lahni, Jannic Hartwecker, Matthew D. Kuchem, Mirko Walter-Huber, N. Vortmeier, Tim Delbrügger, Ümit Güler, Igor Vatolkin, M. Preuss

引用次数: 18

Evolving both search and strategy for Reversi players using genetic programming 利用遗传程序进化逆向棋手的搜索和策略

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374137

Amit Benbassat, M. Sipper

引用次数: 10

Towards adaptive online RTS AI with NEAT 基于NEAT的自适应在线RTS AI

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374187

Jason M. Traish, J. Tulip

引用次数: 10

Simulation-based optimization of StarCraft tactical AI through evolutionary computation 基于进化计算的星际争霸战术AI仿真优化

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374182

N. Othman, James Decraene, Wentong Cai, Nan Hu, M. Low, A. Gouaillard

引用次数: 27

Applying reinforcement learning to small scale combat in the real-time strategy game StarCraft:Broodwar 将强化学习应用于即时战略游戏《星际争霸:母巢之战》中的小规模战斗

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374183

S. Wender, I. Watson

引用次数: 104

In-game action list segmentation and labeling in real-time strategy games 即时策略游戏中的游戏内动作列表分割和标签

2012 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2012-12-06 DOI: 10.1109/CIG.2012.6374150

Wei Gong, Ee-Peng Lim, Palakorn Achananuparp, Feida Zhu, D. Lo, Freddy Chongtat Chua

引用次数: 5