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2009 IEEE Symposium on Computational Intelligence and Games

7-10 Sept. 2009

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  • 2009 IEEE Symposium on Cumputational Intelligence and Games

    Publication Year: 2009, Page(s): 1
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  • Preface

    Publication Year: 2009, Page(s): 1
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  • Sponsors

    Publication Year: 2009
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  • Acknowledgements

    Publication Year: 2009
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  • Table of contents

    Publication Year: 2009, Page(s):1 - 4
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  • Organizing Committee

    Publication Year: 2009, Page(s): 1
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  • Programme Committee

    Publication Year: 2009, Page(s): 1
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  • Artificial intelligence in racing games

    Publication Year: 2009, Page(s): 1
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1244 KB)

    Summary form only given. A key aspect in the development of computer games is the behavior of non-player characters. Each type of game poses different challenges for the development of a successful artificial intelligence. In racing games, this translates into the programming of an AI which can adapt to the driving style and to the driving capabilities of the human player so as to improve its gami... View full abstract»

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  • General game-playing systems

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1244 KB)

    The aim of General Game Playing (GGP) is to create intelligent agents that can automatically learn how to play a wide variety of different games at an expert level without any human intervention. This requires that the agents be capable of learning diverse game-playing strategies from basic game rules without any game-specific knowledge being provided by their developers. A successful realization ... View full abstract»

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  • AI isn't just for players: AI-based authoring tools

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1720 KB)

    Game AI research has successfully focused on improving the player experience, creating better tactical and strategic opponents, more convincing non-player characters, better path-finding approaches, and so on. However, as we create richer AI-based experiences for players, we can not forget authors. Human authors must be able to craft game experiences, creating the richness and nuances that make ga... View full abstract»

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  • Practical issues in evolving neural network controllers for video game agents

    Publication Year: 2009, Page(s): 1
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1036 KB)

    This tutorial will draw upon a significant accumulation of practical knowledge that is rarely explained comprehensively in research publications or textbooks to illuminate how evolutionary algorithms can be combined effectively with neural networks in video games. View full abstract»

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  • Modeling and simulation framework of real urban and board games to train players

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1087 KB)

    This tutorial will include: (1) a modeling approach for generating an urban terrain model from a Compact Terrain DataBase (CTDB) for computer-simulation of an urban search and rescue operation (US&RO), (2) a modeling approach for implementing the game RISK and generating autonomous players (3) a generalized implementation strategy for integrating both models into an autonomous dynamic plan... View full abstract»

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  • Defcon

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1226 KB)

    The aim of the CIG 2009 Defcon AI competition is to see which bot is the best Defcon player. Each bot plays 30 matches against each other bot, in a series of one-on-one matches with bots playing in each of the possible starting territory configurations. The game will run on a limited-information mode (i.e., bots cannot see units hidden by the fog of war) and the victory timer will start no later t... View full abstract»

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  • Screen-capture Ms Pac-Man

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1226 KB)

    Ms. Pac-Man is a challenging and interesting game that is usually viewed form the perspective of the Ms. Pac-Man agent. The game also provides an excellent environment for testing multi-agent strategies for controlling the team of ghosts, with the aim either of optimising the playability of the game, or simply to minimise the score obtained by the agent. It is this latter more measurable objective... View full abstract»

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  • Mario AI competition

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1636 KB)

    This competition is about learning, or otherwise developing, the best controller (agent) for a version of Super Mario Bros. View full abstract»

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  • Simulated car racing

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1636 KB)

    The simulated car racing competition of CIG-2009 is the final event of the 2009 Simulated Car Racing Championship, an event joining the three competitions held at CEC-2009, GECCO-2009, and CIG-2009. View full abstract»

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  • The 2K BotPrize

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1058 KB)

    The aim of the contest is to see if a computer game playing bot can play like a human. In the contest, bots try to convince a panel of expert judges that they are actually human players. Computers are superbly fast and accurate at playing games, but can they be programmed to be more fun to play - to play like you and me? People like to play against opponents who are like themselves - opponents wit... View full abstract»

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  • Ms Pac-Man versus ghost-team competition

    Publication Year: 2009, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1058 KB)

    Ms. Pac-Man is a challenging and interesting game that is usually viewed form the perspective of the Ms. Pac-Man agent. The game is also provides an excellent environment for testing multi-agent strategies for controlling the team of ghosts, with the aim either of optimising the playability of the game, or simply to minimise the score obtained by the agent. It is this latter more measurable object... View full abstract»

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  • Author index

    Publication Year: 2009, Page(s): 1
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  • Player modeling using self-organization in Tomb Raider: Underworld

    Publication Year: 2009, Page(s):1 - 8
    Cited by:  Papers (31)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1338 KB) | HTML iconHTML

    We present a study focused on constructing models of players for the major commercial title Tomb Raider: Underworld (TRU). Emergent self-organizing maps are trained on high-level playing behavior data obtained from 1365 players that completed the TRU game. The unsupervised learning approach utilized reveals four types of players which are analyzed within the context of the game. The proposed appro... View full abstract»

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  • Monte Carlo search applied to card selection in Magic: The Gathering

    Publication Year: 2009, Page(s):9 - 16
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (351 KB) | HTML iconHTML

    We present the card game magic: the gathering as an interesting test bed for AI research. We believe that the complexity of the game offers new challenges in areas such as search in imperfect information domains and opponent modelling. Since there are a thousands of possible cards, and many cards change the rules to some extent, to successfully build AI for magic: the gathering ultimately requires... View full abstract»

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  • Iterated Prisoner's Dilemma for species

    Publication Year: 2009, Page(s):17 - 24
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (228 KB) | HTML iconHTML

    The Iterated Prisoner's Dilemma (IPD) is widely used to study the evolution of cooperation between self-interested agents. Existing work asks how genes that code for cooperation arise and spread through a single-species population of IPD playing agents. In this paper, we focus on competition between different species of agents. Making this distinction allows us to separate and examine macroevoluti... View full abstract»

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  • Deceptive strategies for the evolutionary minority game

    Publication Year: 2009, Page(s):25 - 31
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (347 KB) | HTML iconHTML

    The evolutionary minority game is extensively used to study adaptive behavior in a population of interacting agents. In time the agents self-organize despite the fact agents act independently in choosing how to play the game and do not know the play of any other agent. In this paper we study agents who collude with each other to play the same strategy. However, nothing prevents agents from being d... View full abstract»

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  • Temporal difference learning with interpolated table value functions

    Publication Year: 2009, Page(s):32 - 37
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (209 KB) | HTML iconHTML

    This paper introduces a novel function approximation architecture especially well suited to temporal difference learning. The architecture is based on using sets of interpolated table look-up functions. These offer rapid and stable learning, and are efficient when the number of inputs is small. An empirical investigation is conducted to test their performance on a supervised learning task, and on ... View full abstract»

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  • Improving Temporal Difference game agent control using a dynamic exploration during control learning

    Publication Year: 2009, Page(s):38 - 45
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (676 KB) | HTML iconHTML

    This paper investigates the use of a dynamically generated exploration rate when using a reinforcement learning-based game agent controller within a dynamic digital game environment. Temporal difference learning has been employed for the real-time generation of reactive game agent behaviors within a variation of classic arcade game Pac-Man. Due to the dynamic nature of the game environment initial... View full abstract»

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