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2015 IEEE Conference on Computational Intelligence and Games (CIG)最新文献

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The geometry friends game AI competition 几何之友游戏AI竞赛
2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-08-01 DOI: 10.1109/CIG.2015.7317949
R. Prada, Phil Lopes, João Catarino, Joao Quiterio, Francisco S. Melo
{"title":"The geometry friends game AI competition","authors":"R. Prada, Phil Lopes, João Catarino, Joao Quiterio, Francisco S. Melo","doi":"10.1109/CIG.2015.7317949","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317949","url":null,"abstract":"This paper describes a new game AI competition that engages participants in the creation of agents for a cooperative platform puzzle game. The agents face the challenge of acting in a dynamic environment, with friction and gravity, as they coordinate actions to solve cooperative puzzles. Hence, agents need to devise cooperative plans to solve the puzzles in the most efficient way and to coordinate their actions to perform joint actions in real-time. The core of the competition is the cooperative track that requires the development of two distinct agents, but we also include a single player track for participants that want to craft the basic skills of the agent without the complexity of cooperation. In particular, to cope with understanding the topology of a level in order to define a plan for solving the puzzle or to define mechanisms to act well in the physics-based game environment. We present the results of the 2014 competition held at IEEE Conference on Computational Intelligence in Games, in Dortmund, and discuss some future directions of research.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124979965","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: 29
Enhancing theme park experiences through adaptive cyber-physical play 通过自适应的网络物理游戏提升主题公园体验
2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-08-01 DOI: 10.1109/CIG.2015.7317893
W. Raffe, M. Tamassia, Fabio Zambetta, Xiaodong Li, F. Mueller
{"title":"Enhancing theme park experiences through adaptive cyber-physical play","authors":"W. Raffe, M. Tamassia, Fabio Zambetta, Xiaodong Li, F. Mueller","doi":"10.1109/CIG.2015.7317893","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317893","url":null,"abstract":"In this vision paper we explore the potential for enhancing theme parks through the introduction of adaptive cyber-physical attractions. That is, some physical attraction that is controlled by a digital system, which takes participants' actions as input and, in turn, alters the participants' experiences. This paper is thus divided into three main parts; (1) a look at the types of attractions that a typical theme park may offer and, from this, the identification of a gap in an agency versus structure spectrum that recent research and industry developments are starting to fill; (2) a discussion of the advantages that cyber-physical play has in filling this gap and a few examples of envisioned future attractions; and (3) how such cyber-physical play can uniquely allow for adaptive attractions, whereby the physical attraction is personalized to suit the capabilities or preferences of the current attraction participants, as well as some foreseeable design considerations and challenges in doing so. Through the combination of these three parts, we hope to promote further research into augmenting theme parks with adaptive cyber-physical play attractions.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132505029","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: 6
Toward curling informatics — Digital scorebook development and game information analysis 走向冰壶信息学——数字计分簿开发和游戏信息分析
2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-08-01 DOI: 10.1109/CIG.2015.7317911
Fumito Masui, Hiroki Ueno, H. Yanagi, M. Ptaszynski
{"title":"Toward curling informatics — Digital scorebook development and game information analysis","authors":"Fumito Masui, Hiroki Ueno, H. Yanagi, M. Ptaszynski","doi":"10.1109/CIG.2015.7317911","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317911","url":null,"abstract":"This paper introduces the concept of curling informatics and the digital scorebook system iCE which was developed to support strategies and tactics in curling - a winter team sport played on ice. Our project aims to develop an environment to support curling strategies and tactics by realizing methods to record game information, analyzing, visualizing and sharing the information. We developed the digital scorebook system iCE (intelligent Curling Elicitator) as the first step of our concept. We tested our system by recording real game information at the top-level championships. Consequently, we confirmed that the system performs adequately for practical use. Moreover, we analyzed the recorded information in detail, and the results suggest differences in shot accuracies relating to the differences in game scores. This suggests that our proposed method can effectively support strategic/tactical planning in curling games.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131302583","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: 6
An improved approach to reinforcement learning in Computer Go 一种改进的计算机围棋强化学习方法
2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-08-01 DOI: 10.1109/CIG.2015.7317910
Michael Dann, Fabio Zambetta, John Thangarajah
{"title":"An improved approach to reinforcement learning in Computer Go","authors":"Michael Dann, Fabio Zambetta, John Thangarajah","doi":"10.1109/CIG.2015.7317910","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317910","url":null,"abstract":"Monte-Carlo Tree Search (MCTS) has revolutionized, Computer Go, with programs based on the algorithm, achieving a level of play that previously seemed decades away., However, since the technique involves constructing a search tree, its performance tends to degrade in larger state spaces. Dyna-2, is a hybrid approach that attempts to overcome this shortcoming, by combining Monte-Carlo methods with state abstraction. While, not competitive with the strongest MCTS-based programs, the, Dyna-2-based program RLGO achieved the highest ever rating, by a traditional program on the 9×9 Computer Go Server. Plain, Dyna-2 uses _-greedy exploration and a flat learning rate, but we, show that the performance of the algorithm can be significantly, improved by making some relatively minor adjustments to this, configuration. Our strongest modified program achieved an Elo, rating 289 points higher than the original in head-to-head play, equivalent to an expected win rate of 84%.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131650439","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: 1
Depth, balancing, and limits of the Elo model Elo模型的深度、平衡和限制
2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-08-01 DOI: 10.1109/CIG.2015.7317964
M. Cauwet, O. Teytaud, T. Cazenave, Abdallah Saffidine, Hua-Min Liang, Shi-Jim Yen, Hung-Hsuan Lin, I-Chen Wu
{"title":"Depth, balancing, and limits of the Elo model","authors":"M. Cauwet, O. Teytaud, T. Cazenave, Abdallah Saffidine, Hua-Min Liang, Shi-Jim Yen, Hung-Hsuan Lin, I-Chen Wu","doi":"10.1109/CIG.2015.7317964","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317964","url":null,"abstract":"Much work has been devoted to the computational complexity of games. However, they are not necessarily relevant for estimating the complexity in human terms. Therefore, human-centered measures have been proposed, e.g. the depth. This paper discusses the depth of various games, extends it to a continuous measure. We provide new depth results and present tool (given-first-move, pie rule, size extension) for increasing it. We also use these measures for analyzing games and opening moves in Y, NoGo, Killall Go, and the effect of pie rules.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128106986","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: 4
Job-level UCT search for solving Hex 作业级UCT搜索解决Hex
2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-08-01 DOI: 10.1109/CIG.2015.7317908
Xi Liang, Ting-Han Wei, I-Chen Wu
{"title":"Job-level UCT search for solving Hex","authors":"Xi Liang, Ting-Han Wei, I-Chen Wu","doi":"10.1109/CIG.2015.7317908","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317908","url":null,"abstract":"Recently, Pawlewicz and Hayward successfully solved many Hex openings based on the Scalable Parallel Depth-First Proof-Number Search algorithm (SPDFPN), which was performed in a single machine with multiple threads. However, further parallelization is limited by the number of cores a single machine can possess. This paper investigates adapting this SPDFPN solver to a distributed computing environment, using the previously proposed job-level upper-confidence tree algorithm (JL-UCT) in order to further increase parallelism. To improve on the adapted JL-UCT solver system, we make a new attempt to support transposition information sharing among jobs in JL implementations. A mix of shared-memory and database techniques was used to achieve this improvement. Our experiments show that the adapted JL-UCT solver scales for larger problems. Additionally, using a single machine with 24 cores, the adapted method is able to solve Hex openings with less time than the previous SPDFPN solver in three of four test cases. Overall, for the four test cases, the adapted JL-UCT solver, using 6 nodes each with 24 cores, obtained speedups of 1.6, 1.9, 1.8 and 2.6 over those for the SPDFPN solver using one node with 24 cores.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128440869","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: 3
Digital curling strategy based on game tree search 基于游戏树搜索的数字冰壶策略
2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-08-01 DOI: 10.1109/CIG.2015.7317931
Masahito Yamamoto, Shu Kato, H. Iizuka
{"title":"Digital curling strategy based on game tree search","authors":"Masahito Yamamoto, Shu Kato, H. Iizuka","doi":"10.1109/CIG.2015.7317931","DOIUrl":"https://doi.org/10.1109/CIG.2015.7317931","url":null,"abstract":"Strategy for digital curling based on the game tree search is demonstrated. Digital curling has been developed for simulating curling which is one of the winter sports. We present a curling playing program run on the digital curling simulator. It enable us to decide the direction and the speed of the stone to be delivered for maximizing the evaluation values of resultant game states. The novel evaluation function is constructed and the effective method for reducing the simulation trials is proposed for finding the best shot on the current game state. Our experimental results reveal that our proposed program outperforms the previous rule-based program and competes with the MonteCarlo based program.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121598522","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
Tutorial III: Evolving neural networks 教程三:进化的神经网络
2015 IEEE Conference on Computational Intelligence and Games (CIG) Pub Date : 2015-07-11 DOI: 10.1145/2739482.2756577
Risto Miikkulainen
{"title":"Tutorial III: Evolving neural networks","authors":"Risto Miikkulainen","doi":"10.1145/2739482.2756577","DOIUrl":"https://doi.org/10.1145/2739482.2756577","url":null,"abstract":"Summary form only given. Neuroevolution, i.e. evolution of artificial neural networks, has recently emerged as a powerful technique for solving challenging reinforcement learning problems. Compared to traditional (e.g. value-function based) methods, neuroevolution is especially strong in domains where the state of the world is not fully known: The state can be disambiguated through recurrency, and novel situations handled through pattern matching. In this tutorial, I will review (1) neuroevolution methods that evolve fixedtopology networks, network topologies, and network construction processes, (2) ways of combining traditional neural network learning algorithms with evolutionary methods, and (3) applications of neuroevolution to creating intelligent agents in games.","PeriodicalId":244862,"journal":{"name":"2015 IEEE Conference on Computational Intelligence and Games (CIG)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115601223","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
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