2015 IEEE Conference on Computational Intelligence and Games (CIG)

Aug. 31 2015-Sept. 2 2015

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  • Keynote speech I: Co-evolutionary learning in game-playing

    Publication Year: 2015, Page(s): 16
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  • Keynote speech II: General video game AI: Challenges and applications

    Publication Year: 2015, Page(s): 17
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  • Keynote speech III: Computer go research — The challenges ahead

    Publication Year: 2015, Page(s): 18
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  • Keynote speech IV: Where games meet hyper-heuristics

    Publication Year: 2015, Page(s): 19
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  • Tutorial I: Video Game Description Language (VGDL) and the challenge of creating agents for General Video Game Playing (GVGP)

    Publication Year: 2015, Page(s): 20
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (388 KB) | HTML iconHTML

    Games have attracted many AI researchers over the last decades, allowing to benchmark multiple and varied simulated environments to test AI algorithms in. It is not rare that information about the game played is supplied in order to help the algorithm to achieve better results. This may pose a problem: in some cases it is debatable if the success of a given technique is due to the algorithm itself... View full abstract»

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  • Tutorial II: Representations for evolutionary computation in games

    Publication Year: 2015, Page(s): 21
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (385 KB) | HTML iconHTML

    Representation is a central issue in evolutionary computation. The no free lunch theorem demonstrates that there is no intrinsic advantage in a particular algorithm when considered against complete spaces of problems. The corollary is that algorithms should be fitted to the problems they are solving. Choice of representation is the primary point in the design of an evolutionary algorithm where the... View full abstract»

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  • Tutorial III: Evolving neural networks

    Publication Year: 2015, Page(s): 22
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (350 KB) | HTML iconHTML

    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... View full abstract»

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  • Author index

    Publication Year: 2015, Page(s):553 - 557
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  • Competitions

    Publication Year: 2015, Page(s):550 - 552
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  • [Copyright notice]

    Publication Year: 2015, Page(s): 2
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  • [Front cover]

    Publication Year: 2015, Page(s): 1
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  • Conference Organization

    Publication Year: 2015, Page(s):13 - 14
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  • Preface

    Publication Year: 2015, Page(s):11 - 12
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  • Systems for player reputation with NPC agents

    Publication Year: 2015, Page(s):546 - 547
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (99 KB) | HTML iconHTML

    This paper examines how current methods of reputation from applications such as social networks could be applied to single player games. This allows for a more realistic transfer of information between Non-Player Characters (NPCs) allowing them to act within the narrative with expected behaviors. Current information transfers are examined and demonstrate an omnipresent and instantaneous transmissi... View full abstract»

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  • “RehabConnex”: A middleware for the flexible connection of multimodal game applications with input devices used in movement therapy and physical exercising

    Publication Year: 2015, Page(s):496 - 502
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1994 KB) | HTML iconHTML

    “RehabConnex” is a middleware product, developed specifically to facilitate communication between hardware devices and multimodal game applications used in movement therapy and physical exercise. “RehabConnex“ is the core key development of the “IMIC”-project (Innovative Movement Therapy in Childhood), created by an interdisciplinary team of university par... View full abstract»

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  • Prediction as faster perception in a real-time fighting video game

    Publication Year: 2015, Page(s):517 - 522
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (163 KB) | HTML iconHTML

    In a real-time video game, AI-controlled players, called agents, are still inferior to skilled human players on equal footing. In this work, we aim to construct a strong agent enough to fight with skilled human players in a real-time fighting video game. First we investigate the relation between perception speed and performance. From a simulation using two agents one of which has delayed perceptio... View full abstract»

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  • Enhancing theme park experiences through adaptive cyber-physical play

    Publication Year: 2015, Page(s):503 - 510
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (149 KB) | HTML iconHTML

    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 ... View full abstract»

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  • Optimization of Angry Birds AI controllers with distributed computing

    Publication Year: 2015, Page(s):544 - 545
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (183 KB) | HTML iconHTML

    The one of important issues in artificial intelligence (AI) research is the development of AI for games because of its difficulty. To promote the research on video games AI, there have been several game AI competitions. However, some games with physics engine (geometry friends or Angry Birds) have no support on the prediction of future events using simulation. It makes much difficult to build AI f... View full abstract»

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  • Interpreting behaviors of mobile game players from in-game data and context logs

    Publication Year: 2015, Page(s):548 - 549
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1085 KB) | HTML iconHTML

    Human behaviors can be interpreted based on its routine activities. Since, mobile phones are very common now-a-days, the activities performed on a mobile phone can be an effective tool to judge the behavior of an individual. In this paper, we interpret the behavior of different individuals playing a mobile video game. For this purpose, we developed a “Shoot them up” android based vid... View full abstract»

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  • MCTS with influence map for general video game playing

    Publication Year: 2015, Page(s):534 - 535
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (197 KB) | HTML iconHTML

    In the General Video Game-AI competition in 2014 IEEE Computational Intelligence in Games, Monte Carlo Tree Search (MCTS) outperformed other alternatives. Interestingly, the sample MCTS ranked in the third place. However, MCTS was not always perfect in this problem. For example, it cannot explore enough search space of video games because of time constraints. As a result, if the AI player receives... View full abstract»

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  • Mining game logs to create a playbook for unit AIs

    Publication Year: 2015, Page(s):391 - 398
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4453 KB) | HTML iconHTML

    We present a method for mining game logs for plays, sequences of actions for a group of units achieving an objective with a high likelihood and in many logs. The mining moves through a log backwards, identifying states that achieve the objective and taking this state and certain surrounding ones as a play candidate. After filtering out irrelevant information and too costly candidates, we cluster s... View full abstract»

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  • Combining pathfmding algorithm with Knowledge-based Monte-Carlo tree search in general video game playing

    Publication Year: 2015, Page(s):523 - 529
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (538 KB) | HTML iconHTML

    This paper proposes a general video game playing AI that combines a pathfmding algorithm with Knowledge-based Fast-Evolutionary Monte-Carlo tree search (KB Fast-Evo MCTS). This AI is able to acquire knowledge of the game through simulation, select suitable targets on the map using the acquired knowledge, and head to the target in an efficient manner. In addition, improvements have been proposed to... View full abstract»

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  • Testing reliability of replay-based imitation for StarCraft

    Publication Year: 2015, Page(s):536 - 537
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (238 KB) | HTML iconHTML

    For StarCraft, it's easy to download lots of replays from gaming portals. Using simple tools, it's possible to extract all the gaming events stored in the replays. At each frame, it can tell us the human player's decision making given game states. Instead of making hard-coded AIs, it's promising to imitate the human player's decision recorded in the replays. In this study, we propose to create an ... View full abstract»

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  • Mobile EEG & ECG integration system for monitoring physiological states in peforming simulated war game training

    Publication Year: 2015, Page(s):542 - 543
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (365 KB) | HTML iconHTML

    It is interesting to measure the player's physiological states when playing the exciting war game in the simulated platform. Fresh soldiers are usually asked to perform the simulated shooting task in the military training. However, it is lack to understand the soldier's physiological states, especially he is under threaten, high tension, or big challenge situation. This study intends to develop a ... View full abstract»

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  • Generation of an arbitrary shaped large maze by assembling mazes

    Publication Year: 2015, Page(s):538 - 539
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (446 KB) | HTML iconHTML

    Lots of games have used maze generation for their maps, geographical features or terrains. Previously, they used spanning tree algorithms, growing tree algorithm, and so on. However, the methods placed restrictions on the shape of mazes and used fixed matrices. In this paper, we propose a simple and easy way to generate an arbitrary shaped maze by assembling mazes. Because it's possible to selecti... View full abstract»

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