IEEE Transactions on Computational Intelligence and AI in Games最新文献_第4页

Coevolutionary CMA-ES for Knowledge-Free Learning of Game Position Evaluation 博弈位置评估无知识学习的协同进化CMA-ES

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-12-01 DOI: 10.1109/TCIAIG.2015.2464711

Wojciech Jaśkowski, M. Szubert

{"title":"Coevolutionary CMA-ES for Knowledge-Free Learning of Game Position Evaluation","authors":"Wojciech Jaśkowski, M. Szubert","doi":"10.1109/TCIAIG.2015.2464711","DOIUrl":"https://doi.org/10.1109/TCIAIG.2015.2464711","url":null,"abstract":"One weakness of coevolutionary algorithms observed in knowledge-free learning of strategies for adversarial games has been their poor scalability with respect to the number of parameters to learn. In this paper, we investigate to what extent this problem can be mitigated by using Covariance Matrix Adaptation Evolution Strategy, a powerful continuous optimization algorithm. In particular, we employ this algorithm in a competitive coevolutionary setup, denoting this setting as Co-CMA-ES. We apply it to learn position evaluation functions for the game of Othello and find out that, in contrast to plain (co)evolution strategies, Co-CMA-ES learns faster, finds superior game-playing strategies and scales better. Its advantages come out into the open especially for large parameter spaces of tens of hundreds of dimensions. For Othello, combining Co-CMA-ES with experimentally-tuned derandomized systematic n-tuple networks significantly improved the current state of the art. Our best strategy outperforms all the other Othello 1-ply players published to date by a large margin regardless of whether the round-robin tournament among them involves a fixed set of initial positions or the standard initial position but randomized opponents. These results show a large potential of CMA-ES-driven coevolution, which could be, presumably, exploited also in other games.","PeriodicalId":49192,"journal":{"name":"IEEE Transactions on Computational Intelligence and AI in Games","volume":"8 1","pages":"389-401"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TCIAIG.2015.2464711","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62593202","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: 7

Guest Editorial Real-Time Strategy Games 客座编辑实时策略游戏

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-12-01 DOI: 10.1109/TCIAIG.2016.2601116

M. Buro, Santiago Ontañón, M. Preuss

引用次数: 0

Intentionality and Conflict in The Best Laid Plans Interactive Narrative Virtual Environment 最佳计划互动叙事虚拟环境中的意向性和冲突

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-12-01 DOI: 10.1109/TCIAIG.2015.2489159

Stephen G. Ware, R. Young

引用次数: 16

Hybrid Pathfinding in StarCraft 《星际争霸》中的混合寻径

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-12-01 DOI: 10.1109/TCIAIG.2015.2414447

Johan Hagelbäck

引用次数: 18

Statistical Relational Learning for Game Theory 博弈论的统计关系学习

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-12-01 DOI: 10.1109/TCIAIG.2015.2490279

Marco Lippi

引用次数: 3

Multiscale Bayesian Modeling for RTS Games: An Application to StarCraft AI RTS游戏的多尺度贝叶斯建模:在星际争霸AI中的应用

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-12-01 DOI: 10.1109/TCIAIG.2015.2487743

Gabriel Synnaeve, P. Bessière

引用次数: 31

Calculating Ultrastrong and Extended Solutions for Nine Men’s Morris, Morabaraba, and Lasker Morris 计算九个男子莫里斯，Morabaraba和Lasker莫里斯的超强和扩展解

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-09-01 DOI: 10.1109/TCIAIG.2015.2420191

G. Gévay, Gábor Danner

{"title":"Calculating Ultrastrong and Extended Solutions for Nine Men’s Morris, Morabaraba, and Lasker Morris","authors":"G. Gévay, Gábor Danner","doi":"10.1109/TCIAIG.2015.2420191","DOIUrl":"https://doi.org/10.1109/TCIAIG.2015.2420191","url":null,"abstract":"The strong solutions of Nine Men's Morris and its variant, Lasker Morris, are well-known results (the starting positions are draws). We reexamined both of these games, and calculated extended strong solutions for them. By this, we mean the game-theoretic values of all possible game states that could be reached from certain starting positions where the number of stones to be placed by the players is different from the standard rules. These were also calculated for a previously unsolved third variant, Morabaraba, with interesting results: most of the starting positions where the players can place an equal number of stones (including the standard starting position) are wins for the first player (as opposed to the above games, where these are usually draws). We also developed a multivalued retrograde analysis, and used it as a basis for an algorithm for solving these games ultra-strongly. This means that when our program is playing against a fallible opponent, it has a greater chance of achieving a better result than the game-theoretic value, compared to randomly selecting between “just strongly” optimal moves. Previous attempts on ultrastrong solutions used local heuristics or learning during games, but we incorporated our algorithm into the retrograde analysis.","PeriodicalId":49192,"journal":{"name":"IEEE Transactions on Computational Intelligence and AI in Games","volume":"8 1","pages":"256-267"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TCIAIG.2015.2420191","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62592567","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

Optimization Using Boundary Lookup Jump Point Search 使用边界查找跳跃点搜索优化

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-09-01 DOI: 10.1109/TCIAIG.2015.2421493

Jason M. Traish, J. Tulip, W. Moore

{"title":"Optimization Using Boundary Lookup Jump Point Search","authors":"Jason M. Traish, J. Tulip, W. Moore","doi":"10.1109/TCIAIG.2015.2421493","DOIUrl":"https://doi.org/10.1109/TCIAIG.2015.2421493","url":null,"abstract":"Cache-based path-finding algorithms lose much of their advantage in dynamic environments where fast online search algorithms are required. Jump point search (JPS) is such a fast algorithm. It works by eliminating most map nodes from evaluation during path expansion. Boundary lookup jump point search (BL-JPS) is a modification that improves the speed of JPS. BL-JPS records the positions of obstacle boundaries and uses these via direct lookup to eliminate much of the iteration involved in searching for jump points in the JPS algorithm. Two sets of experiments are presented, demonstrating the effects of BL-JPS in both static and dynamic environments. The effects of different approaches to cache rebuilding for JPS+ in dynamic environments are also evaluated. Results show that BL-JPS is generally much faster than JPS. It is slower than JPS+ in static environments, but in dynamic environments, BL-JPS outperforms JPS+ for a single search. When multiple paths are searched, the effects of cache rebuilding gradually dominate the effects of search speed, resulting in JPS+ again becoming faster. However, combining JPS+ with BL-JPS provides a very fast path-finding algorithm (BL-JPS+) that outperforms JPS+ over a range of map types and numbers of paths searched.","PeriodicalId":49192,"journal":{"name":"IEEE Transactions on Computational Intelligence and AI in Games","volume":"17 1","pages":"268-277"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TCIAIG.2015.2421493","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62592643","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: 10

The 2014 General Video Game Playing Competition 2014年通用电子游戏比赛

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-09-01 DOI: 10.1109/TCIAIG.2015.2402393

Diego Perez Liebana, Spyridon Samothrakis, J. Togelius, T. Schaul, S. Lucas, Adrien Couëtoux, Jerry Lee, Chong-U Lim, Tommy Thompson

{"title":"The 2014 General Video Game Playing Competition","authors":"Diego Perez Liebana, Spyridon Samothrakis, J. Togelius, T. Schaul, S. Lucas, Adrien Couëtoux, Jerry Lee, Chong-U Lim, Tommy Thompson","doi":"10.1109/TCIAIG.2015.2402393","DOIUrl":"https://doi.org/10.1109/TCIAIG.2015.2402393","url":null,"abstract":"This paper presents the framework, rules, games, controllers, and results of the first General Video Game Playing Competition, held at the IEEE Conference on Computational Intelligence and Games in 2014. The competition proposes the challenge of creating controllers for general video game play, where a single agent must be able to play many different games, some of them unknown to the participants at the time of submitting their entries. This test can be seen as an approximation of general artificial intelligence, as the amount of game-dependent heuristics needs to be severely limited. The games employed are stochastic real-time scenarios (where the time budget to provide the next action is measured in milliseconds) with different winning conditions, scoring mechanisms, sprite types, and available actions for the player. It is a responsibility of the agents to discover the mechanics of each game, the requirements to obtain a high score and the requisites to finally achieve victory. This paper describes all controllers submitted to the competition, with an in-depth description of four of them by their authors, including the winner and the runner-up entries of the contest. The paper also analyzes the performance of the different approaches submitted, and finally proposes future tracks for the competition.","PeriodicalId":49192,"journal":{"name":"IEEE Transactions on Computational Intelligence and AI in Games","volume":"8 1","pages":"229-243"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TCIAIG.2015.2402393","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62592846","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: 193

Comparing Heterogeneous and Homogeneous Flocking Strategies for the Ghost Team in the Game of Ms. Pac-Man 比较《吃豆女士》中幽灵团队的异质和同质群集策略

IEEE Transactions on Computational Intelligence and AI in Games Pub Date : 2016-09-01 DOI: 10.1109/TCIAIG.2015.2425795

F. Liberatore, A. García, P. Castillo, J. J. M. Guervós

引用次数: 4