IEEE Transactions on Computational Intelligence and AI in Games

Issue 1 • March 2014

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Displaying Results 1 - 14 of 14
  • Table of contents

    Publication Year: 2014, Page(s): C1
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  • IEEE Transactions on Computational Intelligence and AI in Games publication information

    Publication Year: 2014, Page(s): C2
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  • General Self-Motivation and Strategy Identification: Case Studies Based on Sokoban and Pac-Man

    Publication Year: 2014, Page(s):1 - 17
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1560 KB) | HTML iconHTML

    In this paper, we use empowerment, a recently introduced biologically inspired measure, to allow an AI player to assign utility values to potential future states within a previously unencountered game without requiring explicit specification of goal states. We further introduce strategic affinity, a method of grouping action sequences together to form “strategies,” by examining the o... View full abstract»

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  • Passing a Hide-and-Seek Third-Person Turing Test

    Publication Year: 2014, Page(s):18 - 30
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2062 KB) | HTML iconHTML

    Hiding and seeking are cognitive abilities frequently demonstrated by humans in both real life and video games. To determine to which extent these abilities can be replicated with AI, we introduce a specialized version of the Turing test for hiding and seeking. We then develop a computer agent that passes the test by appearing indistinguishable from human behavior to a panel of human judges. We an... View full abstract»

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  • Solving the Physical Traveling Salesman Problem: Tree Search and Macro Actions

    Publication Year: 2014, Page(s):31 - 45
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2309 KB) | HTML iconHTML

    This paper presents a number of approaches for solving a real-time game consisting of a ship that must visit a number of waypoints scattered around a 2-D maze full of obstacles. The game, the Physical Traveling Salesman Problem (PTSP), which featured in two IEEE conference competitions during 2012, provides a good balance between long-term planning (finding the optimal sequence of waypoints to vis... View full abstract»

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  • Two Online Learning Playout Policies in Monte Carlo Go: An Application of Win/Loss States

    Publication Year: 2014, Page(s):46 - 54
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1888 KB) | HTML iconHTML

    Recently, Monte Carlo tree search (MCTS) has become the dominant algorithm in Computer Go. This paper compares two simulation algorithms known as playout policies. The base policy includes some mandatory domain-specific knowledge such as seki and urgency patterns, but is still simple to implement. The more advanced learning policy combines two different learning algorithms with those implemented i... View full abstract»

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  • DeepQA Jeopardy! Gamification: A Machine-Learning Perspective

    Publication Year: 2014, Page(s):55 - 66
    Cited by:  Papers (2)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1346 KB) | HTML iconHTML

    DeepQA is a large-scale natural language processing (NLP) question-and-answer system that responds across a breadth of structured and unstructured data, from hundreds of analytics that are combined with over 50 models, trained through machine learning. After the 2011 historic milestone of defeating the two best human players in the Jeopardy! game show, the technology behind IBM Watson, DeepQA, is ... View full abstract»

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  • A Micromanagement Task Allocation System for Real-Time Strategy Games

    Publication Year: 2014, Page(s):67 - 77
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (708 KB) | HTML iconHTML

    Real-time strategy (RTS) game play is a combination of strategy and micromanagement. While strategy is clearly important, the success of a strategy can depend greatly on effective micromanagement. Recent years have seen an increase in work focusing on micromanagement in RTS AI, but the great majority of these works have focused on policies for individual units or very specific situations, while ve... View full abstract»

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  • Procedural Generation of Dungeons

    Publication Year: 2014, Page(s):78 - 89
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1535 KB) | HTML iconHTML

    The use of procedural content generation (PCG) techniques in game development has been mostly restricted to very specific types of game elements. PCG has seldom been deployed for generating entire game levels, a notable exception to this being dungeons: a specific type of game level often encountered in adventure and role playing games. Due to their peculiar combination of pace, gameplay, and game... View full abstract»

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  • IEEE Conference on Computational Intelligence in Games 2014

    Publication Year: 2014, Page(s): 90
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  • Special issue on real-time strategy games

    Publication Year: 2014, Page(s): 91
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  • Technology insight on demand on IEEE.tv

    Publication Year: 2014, Page(s): 92
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  • IEEE Computational Intelligence Society Information

    Publication Year: 2014, Page(s): C3
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  • IEEE Transactions on Computational Intelligence and AI in Games information for authors

    Publication Year: 2014, Page(s): C4
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Aims & Scope

The IEEE Transactions on Computational Intelligence and AI in Games (T-CIAIG) publishes archival journal quality original papers in computational intelligence and related areas in artificial intelligence applied to games, including but not limited to videogames, mathematical games, human–computer interactions in games, and games involving physical objects. Emphasis is placed on the use of these methods to improve performance in and understanding of the dynamics of games, as well as gaining insight into the properties of the methods as applied to games. It also includes using games as a platform for building intelligent embedded agents for the real world. Papers connecting games to all areas of computational intelligence and traditional AI are considered.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Graham Kendall
The University of Nottingham
Jalan Broga, 43500 Semenyih
Selangor Darul Ehsan, Malaysia
Tel.: +6(30) 8924 8306
Fax: +6(30) 8924 8299
graham.kendall@nottingham.ac.uk
http://www.graham-kendall.com

Editorial Assistant
Wendy Knibb
wendy.knibb@gmail.com