Статті в журналах: "Game tree"

1

Pijls, Wim, and Arie de Bruin. "Game tree algorithms and solution trees." Theoretical Computer Science 252, no. 1-2 (February 2001): 197–215. http://dx.doi.org/10.1016/s0304-3975(00)00082-7.

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2

Xiong, Shuo, and Hiroyuki Iida. "Attractiveness of real time strategy games." Computer Science and Information Systems 12, no. 4 (2015): 1217–34. http://dx.doi.org/10.2298/csis141101054x.

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Game refinement idea is a unique theory that has been proposed based on the uncertainty of game outcome. A game refinement measure was derived from the game information progress model and has been applied in the domains such as board games and sports games. The present challenge is to apply the game refinement theory in the domain of RTS games. To do so, we use StarCraft II as a testbed and introduce a concept of strategy tree in order to construct a game tree of a RTS game. Then, game refinement values are calculated and compared with other type of games. It is found that StarCraft II has a zone value of game refinement.

3

Malík, V., and P. Karnet. "Game damage to forest trees." Journal of Forest Science 53, No. 9 (January 7, 2008): 406–12. http://dx.doi.org/10.17221/2143-jfs.

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Humans should behave in such a way that they will not endanger the existence of other living entities. After all, human activities affected the tree species composition and wildlife living conditions. Humans are now responsible for the preservation of delicate equilibrium in nature. Two localities were chosen for the research of game damage caused to standing trees – shooting areas Lužánky and Červený jelen, both situated in the vicinity of Jindřichův Hradec in South Bohemia. Seasonal character of tree-damage origin as well as its relation to the chemical content of spruce (Picea abies [L.] Karst.) and pine (Pinus sylvestris [L.]) bark were investigated. This area is typical of high game stock; trees are damaged by browsing and bark stripping. Particular advice for game management with respect to minimizing tree damage is presented. The data set of chemical bark analyses was statistically evaluated by t- and F-test and significant differences in element contents were detected between damaged and undamaged pine bark for N-substances (P = 0.003309), Ca (P = 0.001460), P (P = 0.004343), Mg (P = 0.001419) and K (P = 0.016290). Humans have influenced many changes in the distribution of different animal and plant species. Among others they are responsible for the altered species composition. Typically the extinction of large predators produces changes in food chains. In forest stands influenced by human activities the reasonable game management and the regulation of game stock seems to be one of the main tools in forest protection.

4

Feldmann, R., B. Monien, P. Mysliwietz, and O. Vornberger. "Distributed Game-Tree Search1." ICGA Journal 12, no. 2 (June 1, 1989): 65–73. http://dx.doi.org/10.3233/icg-1989-12203.

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5

Marsland, T. A., and Fred Popowich. "Parallel Game-Tree Search." IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-7, no. 4 (July 1985): 442–52. http://dx.doi.org/10.1109/tpami.1985.4767683.

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6

Schaeffer, Jonathan. "Distributed game-tree searching." Journal of Parallel and Distributed Computing 6, no. 1 (February 1989): 90–114. http://dx.doi.org/10.1016/0743-7315(89)90044-0.

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7

Novak, Damijan, Domen Verber, Jani Dugonik, and Iztok Fister. "A Comparison of Evolutionary and Tree-Based Approaches for Game Feature Validation in Real-Time Strategy Games with a Novel Metric." Mathematics 8, no. 5 (May 1, 2020): 688. http://dx.doi.org/10.3390/math8050688.

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When it comes to game playing, evolutionary and tree-based approaches are the most popular approximate methods for decision making in the artificial intelligence field of game research. The evolutionary domain therefore draws its inspiration for the design of approximate methods from nature, while the tree-based domain builds an approximate representation of the world in a tree-like structure, and then a search is conducted to find the optimal path inside that tree. In this paper, we propose a novel metric for game feature validation in Real-Time Strategy (RTS) games. Firstly, the identification and grouping of Real-Time Strategy game features is carried out, and, secondly, groups are included into weighted classes with regard to their correlation and importance. A novel metric is based on the groups, weighted classes, and how many times the playtesting agent invalidated the game feature in a given game feature scenario. The metric is used in a series of experiments involving recent state-of-the-art evolutionary and tree-based playtesting agents. The experiments revealed that there was no major difference between evolutionary-based and tree-based playtesting agents.

8

Khmelnitskaya, Anna, Özer Selçuk, and Dolf Talman. "The average covering tree value for directed graph games." Journal of Combinatorial Optimization 39, no. 2 (October 30, 2019): 315–33. http://dx.doi.org/10.1007/s10878-019-00471-5.

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Abstract We introduce a single-valued solution concept, the so-called average covering tree value, for the class of transferable utility games with limited communication structure represented by a directed graph. The solution is the average of the marginal contribution vectors corresponding to all covering trees of the directed graph. The covering trees of a directed graph are those (rooted) trees on the set of players that preserve the dominance relations between the players prescribed by the directed graph. The average covering tree value is component efficient, and under a particular convexity-type condition it is stable. For transferable utility games with complete communication structure the average covering tree value equals to the Shapley value of the game. If the graph is the directed analog of an undirected graph the average covering tree value coincides with the gravity center solution.

9

Chang, Wen-Chih, Te-Hua Wang, and Yan-Da Chiu. "Board Game Supporting Learning Prim’s Algorithm and Dijkstra’s Algorithm." International Journal of Multimedia Data Engineering and Management 1, no. 4 (October 2010): 16–30. http://dx.doi.org/10.4018/jmdem.2010100102.

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The concept of minimum spanning tree algorithms in data structure is difficult for students to learn and to imagine without practice. Usually, learners need to diagram the spanning trees with pen to realize how the minimum spanning tree algorithm works. In this paper, the authors introduce a competitive board game to motivate students to learn the concept of minimum spanning tree algorithms. They discuss the reasons why it is beneficial to combine graph theories and board game for the Dijkstra and Prim minimum spanning tree theories. In the experimental results, this paper demonstrates the board game and examines the learning feedback for the mentioned two graph theories. Advantages summarizing the benefits of combining the graph theories with board game are discussed.

10

Hasanudin, Muhaimin, Turki Salim, and Arkan Nur Robby. "RANCANG BANGUN APLIKASI GAME PUZZLE BERBASIS ANDROID MENGGUNAKAN ALGORITMA DECISION TREE." Journal CERITA 3, no. 2 (August 1, 2017): 171–80. http://dx.doi.org/10.33050/cerita.v3i2.654.

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The development of games today is very rapid and has become part of the lifestyle. A puzzle game is an application that can be used to hone thinking and memory skills where users have to find a way out and collect special items that have been provided at every level of the game . The player must collect all the white orb in each level to get the key to move to the next level but the player will be confronted by the constraints on how to find the key and retrieve it . The game is designed using decision tree and game algorithms designed using Game Maker Studio that is applied to Android devices.

11

Vágvölgyi, Sandor. "The Ground Tree Transducer Game." Fundamenta Informaticae 34, no. 1,2 (1998): 175–201. http://dx.doi.org/10.3233/fi-1998-341207.

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12

Li, Liwu, and T. A. Marsland. "Probability-based game tree pruning." Journal of Algorithms 11, no. 1 (March 1990): 27–43. http://dx.doi.org/10.1016/0196-6774(90)90027-c.

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13

de Bruin, Arie, Wim Pijls, and Aske Plaat. "Solution Trees as a Basis for Game-Tree Search." ICGA Journal 17, no. 4 (December 1, 1994): 207–19. http://dx.doi.org/10.3233/icg-1994-17404.

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14

Hong, Tzung-Pei, Ke-Yuan Huang, and Wen-Yang Lin. "Adversarial Search by Evolutionary Computation." Evolutionary Computation 9, no. 3 (September 2001): 371–85. http://dx.doi.org/10.1162/106365601750406046.

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In this paper, we consider the problem of finding good next moves in two-player games. Traditional search algorithms, such as minimax and α-β pruning, suffer great temporal and spatial expansion when exploring deeply into search trees to find better next moves. The evolution of genetic algorithms with the ability to find global or near global optima in limited time seems promising, but they are inept at finding compound optima, such as the minimax in a game-search tree. We thus propose a new genetic algorithm-based approach that can find a good next move by reserving the board evaluation values of new offspring in a partial game-search tree. Experiments show that solution accuracy and search speed are greatly improved by our algorithm.

15

Baum, Eric B., and Warren D. Smith. "Propagating Distributions Up Directed Acyclic Graphs." Neural Computation 11, no. 1 (January 1, 1999): 215–27. http://dx.doi.org/10.1162/089976699300016881.

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In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding on a move after search was completed. In some games, such as chess and Othello, the same position can occur more than once, collapsing the game tree to a directed acyclic graph (DAG). This induces correlations among the distributions at sibling nodes. This article discusses some issues that arise in extending our algorithms to a DAG. We give a simply described algorithm for correctly propagating distributions up a game DAG, taking account of dependencies induced by the DAG structure. This algorithm is exponential time in the worst case. We prove that it is #P complete to propagate distributions up a game DAG correctly. We suggest how our exact propagation algorithm can yield a fast but inexact heuristic.

16

Roberson, Christian, and Katarina Sperduto. "A Monte Carlo Tree Search Player for Birds of a Feather Solitaire." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 9700–9705. http://dx.doi.org/10.1609/aaai.v33i01.33019700.

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Artificial intelligence in games serves as an excellent platform for facilitating collaborative research with undergraduates. This paper explores several aspects of a research challenge proposed for a newly-developed variant of a solitaire game. We present multiple classes of game states that can be identified as solvable or unsolvable. We present a heuristic for quickly finding goal states in a game state search tree. Finally, we introduce a Monte Carlo Tree Search-based player for the solitaire variant that can win almost any solvable starting deal efficiently.

17

Takeuchi, Shogo, Tomoyuki Kaneko, and Kazunori Yamaguchi. "Evaluation of Game Tree Search Methods by Game Records." IEEE Transactions on Computational Intelligence and AI in Games 2, no. 4 (December 2010): 288–302. http://dx.doi.org/10.1109/tciaig.2010.2102022.

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18

Nurhuda, Asep, and Reza Andrea. "PENERAPAN DECISION TREE DALAM AGEN CERDAS "UNDA ANAK PINTAR" PERMAINAN EDUKASI MUATAN LOKAL BAHASA BANJAR." Jurnal Ilmiah Matrik 22, no. 2 (July 27, 2020): 147–52. http://dx.doi.org/10.33557/jurnalmatrik.v22i2.986.

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The educational game "Unda Anak Pintar" is research and development of a puzzle game, it was designed to sharpen memories. In this game, players must read random letters and make words in the Banjar language. Artificial intelligence is also applied in this research. Using the decision tree, game agents can accompany children to play like teachers. The game agent as a virtual teacher can provide sad and happiness emoticon according to the game environment. The results of this study, AI make educational games more interesting and interactive for children.

19

Amarasinghe, S. K., W. L. Goh, and S. He. "Tree decomposition strategy for massively parallel game tree searching." Electronics Letters 34, no. 20 (1998): 1924. http://dx.doi.org/10.1049/el:19981343.

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20

Martin, James B., and Roman Stasiński. "Minimax functions on Galton–Watson trees." Combinatorics, Probability and Computing 29, no. 3 (December 6, 2019): 455–84. http://dx.doi.org/10.1017/s0963548319000403.

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AbstractWe consider the behaviour of minimax recursions defined on random trees. Such recursions give the value of a general class of two-player combinatorial games. We examine in particular the case where the tree is given by a Galton–Watson branching process, truncated at some depth 2n, and the terminal values of the level 2n nodes are drawn independently from some common distribution. The case of a regular tree was previously considered by Pearl, who showed that as n → ∞ the value of the game converges to a constant, and by Ali Khan, Devroye and Neininger, who obtained a distributional limit under a suitable rescaling.For a general offspring distribution, there is a surprisingly rich variety of behaviour: the (unrescaled) value of the game may converge to a constant, or to a discrete limit with several atoms, or to a continuous distribution. We also give distributional limits under suitable rescalings in various cases.We also address questions of endogeny. Suppose the game is played on a tree with many levels, so that the terminal values are far from the root. To be confident of playing a good first move, do we need to see the whole tree and its terminal values, or can we play close to optimally by inspecting just the first few levels of the tree? The answers again depend in an interesting way on the offspring distribution.We also mention several open questions.

21

ALTMAN, EITAN, ODILE POURTALLIER, ALAIN HAURIE, and FRANCESCO MORESINO. "APPROXIMATING NASH EQUILIBRIA IN NONZERO-SUM GAMES." International Game Theory Review 02, no. 02n03 (June 2000): 155–72. http://dx.doi.org/10.1142/s0219198900000123.

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This paper deals with the approximation of Nash equilibria in m-player games. We present conditions under which an approximating sequence of games admits near-equilibria that approximate near-equilibria in the limit game. We apply the results to two classes of games: (i) a duopoly game approximated by a sequence of matrix games, and (ii) a stochastic game played under the S-adapted information structure approximated by games played over a sampled event tree. Numerical illustrations show the usefulness of this approximation theory.

22

Min, Cheng, and Li Yin. "New Characteristic Function for Two Stage Games with Spanning Tree." Contributions to Game Theory and Management 14 (2021): 59–71. http://dx.doi.org/10.21638/11701/spbu31.2021.05.

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Two-stage n-player games with spanning tree are considered. The cooperative behaviour of players is defined. After the first stage, a specified player leaves the game with a probability that depends on the actions of all players in the first stage. A new approach to the construction of the characteristic function is proposed. In the game, all players are connected with the source directly or indirectly. Assume that the players in coalition N \ S have already connected to the source when the players in coalition S ⊂ N wish to connect to the source. The players in coalition S could connect to the source with the help of the players in coalition N \ S. A new characteristic function is de ned in the game, and the Shapley value is constructed. Several results based on the new characteristic function in the two-stage stochastic game are given.

23

Yin, Li, Ovanes Petrosian, and Zou Jinying. "Dynamic Shapley Value in the Game with Perishable Goods." Contributions to Game Theory and Management 14 (2021): 273–89. http://dx.doi.org/10.21638/11701/spbu31.2021.20.

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The paper investigates two-stage stochastic minimum spanning tree games with perishable goods. The cooperative behaviour of the players is defined. At each stage, all players jointly take action to construct a network with a cost matrix. At the second stage, a particular player may leave the game, and the probability of this leaving depends on the cooperative behaviour of all players at the first stage. At each stage game, the total cost of the spanning tree is calculated to include the sum of the costs of the contained edges and the cost of the loss of perishable goods expended on that edge of the spanning tree. The characteristic functions in the game are considered, and the dynamic Shapley values are modified. The time consistency of the dynamic Shapley values is studied.

24

Malík, V., and J. Stuchlý. "Risk factors influencing the probability of browsing by hoofed game on forest trees." Journal of Forest Science 53, No. 8 (January 7, 2008): 359–63. http://dx.doi.org/10.17221/2179-jfs.

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In this paper we analyze how selected risk factors determine the probability of browsing by hoofed game on forest trees. Risk factors covered by the model are: tree species (Norway spruce or Scotch pine), time period (season: spring + summer or autumn + winter) and chemical structure of bark (content of selected nutrients and chemical elements). We use a logit model for these purposes. We formulate the model and perform linear transformation by the natural log. Since the disturbance term in the logit model is heteroscedastic, we cannot use the ordinary least-squares method to estimate the parameters of the model. In this case the maximum likelihood method included in STATGRAPHICS Plus for Windows program is used for its estimation. We use a random sample of data including 59 trees. We do the interpretations of the estimated parameters and other characteristics. We demonstrate how the estimated probabilities depend on the considered factor. The model explains 44.1% of variations of the logits, the model is statistically significant. All regression coefficients are significant at least at 12% confidence level. Among the main explanatory variables (content of P, Ca, NO3, tree species and season), the P and Ca contents in the bark of the tree are the most important factors influencing the probability of future damage to the tree.

25

Yunanto, Septyana Hardianti, and T. Brenda Chandrawati. ""Smart Puzzle" Game Helping Children Learn to Read." SISFORMA 3, no. 1 (February 13, 2017): 13. http://dx.doi.org/10.24167/sisforma.v3i1.677.

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The game is one of the media for learning. One of the games that can be used as media of instruction is "Smart Puzzle" games. "Smart Puzzle" games are educational games are used as tools to teach reading to kindergarten with a game concept devised letters tailored to a different picture in each parts. This game is distinguished into three categories, namely category animals which consists of 10 stage and 2 mini games, a profession category consists of 10 stage and 2 mini games and family categories that consists of 6 stage and 1 mini games. "Smart Puzzle" game has 4 components of games as a medium of instruction. 4 the game components, including drafting letters, complete the picture, match the job with their workplace and learning family tree. With the 4 components of this being the excess of the game "Smart Puzzle" compared to other reading games.

26

PETROSJAN, L. A., and L. V. GRAUER. "STRONG NASH EQUILIBRIUM IN MULTISTAGE GAMES." International Game Theory Review 04, no. 03 (September 2002): 255–64. http://dx.doi.org/10.1142/s0219198902000689.

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Infinite multistage games G with games Γ(·) played on each stage are considered. The definition of path and trajectory in graph tree are introduced. For infinite multistage games G a regularization procedure is introduced and in the regularizied game a strong Nash Equilibrium (coalition proof) is constructed. The approach considered in this paper is similar to one used in the proof of Folk theorems for infinitely repeated games. The repeated n-person "Prisoner's Dilemma" game is considered, as a special case. For this game a strong Nash Equilibrium is found.

27

Yan, Peizhi, and Yi Feng. "Using Convolution and Deep Learning in Gomoku Game Artificial Intelligence." Parallel Processing Letters 28, no. 03 (September 2018): 1850011. http://dx.doi.org/10.1142/s0129626418500111.

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Gomoku is an ancient board game. The traditional approach to solving the Gomoku game is to apply tree search on a Gomoku game tree. Although the rules of Gomoku are straightforward, the game tree complexity is enormous. Unlike many other board games such as chess and Shogun, the Gomoku board state is more intuitive. That is to say, analyzing the visual patterns on a Gomoku game board is fundamental to play this game. In this paper, we designed a deep convolutional neural network model to help the machine learn from the training data (collected from human players). Based on this original neural network model, we made some changes and get two variant neural networks. We compared the performance of the original neural network with its variants in our experiments. Our original neural network model got 69% accuracy on the training data and 38% accuracy on the testing data. Because the decision made by the neural network is intuitive, we also designed a hard-coded convolution-based Gomoku evaluation function to assist the neural network in making decisions. This hybrid Gomoku artificial intelligence (AI) further improved the performance of a pure neural network-based Gomoku AI.

28

Joppen, Tobias, Miriam Ulrike Moneke, Nils Schroder, Christian Wirth, and Johannes Furnkranz. "Informed Hybrid Game Tree Search for General Video Game Playing." IEEE Transactions on Games 10, no. 1 (March 2018): 78–90. http://dx.doi.org/10.1109/tciaig.2017.2722235.

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29

Marsland, T. A. "A Review of Game-Tree Pruning1." ICGA Journal 9, no. 1 (March 1, 1986): 3–19. http://dx.doi.org/10.3233/icg-1986-9102.

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30

Schaeffer, Jonathan. "Experiments in Distributed Game-Tree Searching." ICGA Journal 10, no. 1 (March 1, 1987): 42. http://dx.doi.org/10.3233/icg-1987-10107.

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31

Marsland, T. A. "New Directions in Game-Tree Search." ICGA Journal 12, no. 2 (June 1, 1989): 83. http://dx.doi.org/10.3233/icg-1989-12207.

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32

Schaeffer, Jonathan. "Comment on ‘Distributed Game-Tree Search’." ICGA Journal 12, no. 4 (December 1, 1989): 216–17. http://dx.doi.org/10.3233/icg-1989-12404.

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33

Marsland, T. A. "Single-Agent and Game-Tree Search." ICGA Journal 14, no. 3 (September 1, 1991): 149. http://dx.doi.org/10.3233/icg-1991-14311.

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34

Iida, Hiroyuki. "Heuristic Theories on Game-Tree Search." ICGA Journal 17, no. 4 (December 1, 1994): 220. http://dx.doi.org/10.3233/icg-1994-17407.

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35

Iida, Hiroyuki, Ken-ichi Handa, and Jos Uiterwijk. "Tutoring Strategies in Game-Tree Search." ICGA Journal 18, no. 4 (December 1, 1995): 191–204. http://dx.doi.org/10.3233/icg-1995-18402.

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36

Müller, M. "Global and local game tree search." Information Sciences 135, no. 3-4 (July 2001): 187–206. http://dx.doi.org/10.1016/s0020-0255(01)00136-0.

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37

Marsland, T. A., and Fred Popowich. "Corrections to "Parallel game tree-search''." IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-7, no. 6 (November 1985): 748–49. http://dx.doi.org/10.1109/tpami.1985.4767737.

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38

Björnsson, Y., and T. A. Marsland. "Risk management in game-tree pruning." Information Sciences 122, no. 1 (January 2000): 23–41. http://dx.doi.org/10.1016/s0020-0255(99)00097-3.

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39

Sexton, Thomas R., and Dennis R. Young. "Game Tree Analysis of International Crises." Journal of Policy Analysis and Management 4, no. 3 (1985): 354. http://dx.doi.org/10.2307/3324190.

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40

Brockington, Mark G., and Jonathan Schaeffer. "APHID: Asynchronous Parallel Game-Tree Search." Journal of Parallel and Distributed Computing 60, no. 2 (February 2000): 247–73. http://dx.doi.org/10.1006/jpdc.1999.1600.

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41

Cardinal, Jean, Erik D. Demaine, Samuel Fiorini, Gwenaël Joret, Stefan Langerman, Ilan Newman, and Oren Weimann. "The Stackelberg Minimum Spanning Tree Game." Algorithmica 59, no. 2 (March 21, 2009): 129–44. http://dx.doi.org/10.1007/s00453-009-9299-y.

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42

Orsini, Nicola, Debora Rizzuto, and Nicola Nante. "Introduction to Game-theory Calculations." Stata Journal: Promoting communications on statistics and Stata 5, no. 3 (September 2005): 355–70. http://dx.doi.org/10.1177/1536867x0500500305.

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Анотація:

Game theory can be defined as the study of mathematical models of conflict and cooperation between intelligent and rational decision makers (Myerson 1991). Game-theory concepts apply in economy, sociology, biology, and health care, and whenever the actions of several agents (individuals, groups, or any combination of these) are interdependent. We present a new command gamet to represent the extensive form (game tree) and the strategic form (payoff matrix) of a noncooperative game and to identify the solution of a nonzero and zero-sum game through dominant and dominated strategies, iterated elimination of dominated strategies, and Nash equilibrium in pure and fully mixed strategies. Further, gamet can identify the solution of a zero-sum game through maximin criterion and the solution of an extensive form game through backward induction.

43

Świechowski, Maciej, HyunSoo Park, Jacek Mańdziuk, and Kyung-Joong Kim. "Recent Advances in General Game Playing." Scientific World Journal 2015 (2015): 1–22. http://dx.doi.org/10.1155/2015/986262.

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The goal of General Game Playing (GGP) has been to develop computer programs that can perform well across various game types. It is natural for human game players to transfer knowledge from games they already know how to play to other similar games. GGP research attempts to design systems that work well across different game types, including unknown new games. In this review, we present a survey of recent advances (2011 to 2014) in GGP for both traditional games and video games. It is notable that research on GGP has been expanding into modern video games. Monte-Carlo Tree Search and its enhancements have been the most influential techniques in GGP for both research domains. Additionally, international competitions have become important events that promote and increase GGP research. Recently, a video GGP competition was launched. In this survey, we review recent progress in the most challenging research areas of Artificial Intelligence (AI) related to universal game playing.

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DEPTUŁA, Adam, and Marian PARTYKA. "SIMILARITIES AND DIFFERENCES OF COMPLEX PARAMETRIC GAME TREES FOR INVESTIGATIONS OF DYNAMIC PROPERTIES OF MACHINE SYSTEMS." Scientific Journal of the Military University of Land Forces 165, no. 3 (July 1, 2012): 314–25. http://dx.doi.org/10.5604/01.3001.0002.3506.

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The paper concerns the application of dependence graphs and game tree-structures for the analysis and synthesis of the dynamic properties of machine systems. Graph distributions starting from various beginning vertices are presented in this paper. In order to illustrate the acceptable subsystems of parent machine system, similarities and differences between complex parametric trees are also given. It is also possible to find the part common to all the game tree-structures and describe it over separate design or operational parameters.

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Liu, Lu Si. "Research on Application of the Shortest Path in Game Based on an Improved Genetic Algorithm." Applied Mechanics and Materials 687-691 (November 2014): 1250–53. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1250.

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Nowadays, the game industry has entered a period of vigorous development, each game artificial intelligence has become the indispensable one element, so a good design can be seen as the soul of game, in almost all games have a kind of be good to hear or see appearance, the soul is attracted to the core game player. In this paper, the genetic algorithm becomes a new random search and optimization algorithm, the basic idea of the theory of evolution based on Darwin and Mendel genetics. Genetic algorithm for solving multi objective and complexity with the unpredictable nature of the problem, there is there is nothing comparable to this superiority. The shortest path problem of network is abstracted to a minimum spanning tree problem and the limitations of the minimum spanning tree are analyzed. The notion of the node degree is introduced.

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Wang, Mingyan, Hang Ren, Wei Huang, Taiwei Yan, Jiewei Lei, and Jiayang Wang. "An efficient AI-based method to play the Mahjong game with the knowledge and game-tree searching strategy." ICGA Journal 43, no. 1 (May 26, 2021): 2–25. http://dx.doi.org/10.3233/icg-210179.

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The Mahjong game has widely been acknowledged to be a difficult problem in the field of imperfect information games. Because of its unique characteristics of asymmetric, serialized and multi-player game information, conventional methods of dealing with perfect information games are difficult to be applied directly on the Mahjong game. Therefore, AI (artificial intelligence)-based studies to handle the Mahjong game become challenging. In this study, an efficient AI-based method to play the Mahjong game is proposed based on the knowledge and game-tree searching strategy. Technically, we simplify the Mahjong game framework from multi-player to single-player. Based on the above intuition, an improved search algorithm is proposed to explore the path of winning. Meanwhile, three node extension strategies are proposed based on heuristic information to improve the search efficiency. Then, an evaluation function is designed to calculate the optimal solution by combining the winning rate, score and risk value assessment. In addition, we combine knowledge and Monte Carlo simulation to construct an opponent model to predict hidden information and translate it into available relative probabilities. Finally, dozens of experiments are designed to prove the effectiveness of each algorithm module. It is also worthy to mention that, the first version of the proposed method, which is named as KF-TREE, has won the silver medal in the Mahjong tournament of 2019 Computer Olympiad.

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Liu, Chanjuan, Junming Yan, Yuanye Ma, Tianhao Zhao, Qiang Zhang, and Xiaopeng Wei. "An Adversarial Search Method Based on an Iterative Optimal Strategy." Mathematics 8, no. 9 (September 19, 2020): 1623. http://dx.doi.org/10.3390/math8091623.

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A deeper game-tree search can yield a higher decision quality in a heuristic minimax algorithm. However, exceptions can occur as a result of pathological nodes, which are considered to exist in all game trees and can cause a deeper game-tree search, resulting in worse play. To reduce the impact of pathological nodes on the search quality, we propose an iterative optimal minimax (IOM) algorithm by optimizing the backup rule of the classic minimax algorithm. The main idea is that calculating the state values of the intermediate nodes involves not only the static evaluation function involved but also a search into the future, where the latter is given a higher weight. We experimentally demonstrated that the proposed IOM algorithm improved game-playing performance compared to the existing algorithms.

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Borowiecki, Mieczysław, Anna Fiedorowicz, and Elżbieta Sidorowicz. "Connected domination game." Applicable Analysis and Discrete Mathematics 13, no. 1 (2019): 261–89. http://dx.doi.org/10.2298/aadm171126020b.

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In this paper we introduce a domination game based on the notion of connected domination. Let G = (V,E) be a connected graph of order at least 2. We define a connected domination game on G as follows: The game is played by two players, Dominator and Staller. The players alternate taking turns choosing a vertex of G (Dominator starts). A move of a player by choosing a vertex v is legal, if (1) the vertex v dominates at least one additional vertex that was not dominated by the set of previously chosen vertices and (2) the set of all chosen vertices induces a connected subgraph of G. The game ends when none of the players has a legal move (i.e., G is dominated). The aim of Dominator is to finish as soon as possible, Staller has an opposite aim. Let D be the set of played vertices obtained at the end of the connected domination game (D is a connected dominating set of G). The connected game domination number of G, denoted cg(G), is the minimum cardinality of D, when both players played optimally on G. We provide an upper bound on cg(G) in terms of the connected domination number. We also give a tight upper bound on this parameter for the class of 2-trees. Next, we investigate the Cartesian product of a complete graph and a tree, and we give exact values of the connected game domination number for such a product, when the tree is a path or a star. We also consider some variants of the game, in particular, a Staller-start game.

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Greer, Kieran. "Tree Pruning for New Search Techniques in Computer Games." Advances in Artificial Intelligence 2013 (January 22, 2013): 1–9. http://dx.doi.org/10.1155/2013/357068.

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This paper proposes a new mechanism for pruning a search game tree in computer chess. The algorithm stores and then reuses chains or sequences of moves, built up from previous searches. These move sequences have a built-in forward-pruning mechanism that can radically reduce the search space. A typical search process might retrieve a move from a Transposition Table, where the decision of what move to retrieve would be based on the position itself. This algorithm stores move sequences based on what previous sequences were better, or caused cutoffs. The sequence is then returned based on the current move only. This is therefore position independent and could also be useful in games with imperfect information or uncertainty, where the whole situation is not known at any one time. Over a small set of tests, the algorithm was shown to clearly out perform Transposition Tables, both in terms of search reduction and game-play results. Finally, a completely new search process will be suggested for computer chess or games in general.

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Kar, Anirban. "Axiomatization of the Shapley Value on Minimum Cost Spanning Tree Games." Games and Economic Behavior 38, no. 2 (February 2002): 265–77. http://dx.doi.org/10.1006/game.2001.0883.

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