IEEE Transactions on Computational Intelligence and AI in Games

Issue 1 • March 2015

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Displaying Results 1 - 14 of 14
  • Table of Contents

    Publication Year: 2015, Page(s): C1
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  • IEEE Transactions on Computational Intelligence and AI in Games publication information

    Publication Year: 2015, Page(s): C2
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  • Editorial: IEEE Transactions on Computational Intelligence and AI in Games

    Publication Year: 2015, Page(s):1 - 2
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  • On Cost-Effective Incentive Mechanisms in Microtask Crowdsourcing

    Publication Year: 2015, Page(s):3 - 15
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2273 KB) | HTML iconHTML

    While microtask crowdsourcing provides a new way to solve large volumes of small tasks at a much lower price compared with traditional inhouse solutions, it suffers from quality problems due to the lack of incentives. On the other hand, providing incentives for microtask crowdsourcing is challenging since verifying the quality of submitted solutions is so expensive that it will negate the advantag... View full abstract»

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  • An Enhanced Solver for the Game of Amazons

    Publication Year: 2015, Page(s):16 - 27
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1782 KB) | HTML iconHTML

    The game of Amazons is a modern board game with simple rules and nice mathematical properties. It has a high computational complexity. In 2001, the starting position on a 5 × 5 board was proven to be a first player win. The enhanced Amazons solver presented here extends previous work in the following five ways: by building more powerful endgame databases, including a new type of databases f... View full abstract»

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  • Job-Level Alpha-Beta Search

    Publication Year: 2015, Page(s):28 - 38
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2233 KB) | HTML iconHTML

    An approach called generic job-level (JL) search was proposed to solve computer game applications by dispatching jobs to remote workers for parallel processing. This paper applies JL search to alpha-beta search, and proposes a JL alpha-beta search (JL-ABS) algorithm based on a best-first search version of MTD(f). The JL-ABS algorithm is demonstrated by using it in an opening book analysis for Chin... View full abstract»

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  • Suspenser: A Story Generation System for Suspense

    Publication Year: 2015, Page(s):39 - 52
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1438 KB) | HTML iconHTML

    Interactive storytelling has been receiving a growing attention from AI and game communities and a number of computational approaches have shown promises in generating stories for games. However, there has been little research on stories evoking specific cognitive and affective responses. The goal of the work we describe here is to develop a system that produces a narrative designed specifically t... View full abstract»

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  • Multiple Opponent Optimization of Prisoner’s Dilemma Playing Agents

    Publication Year: 2015, Page(s):53 - 65
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1111 KB) | HTML iconHTML

    Agents for playing iterated prisoner's dilemma are commonly trained using a coevolutionary system in which a player's score against a selection of other members of an evolving population forms the fitness function. In this study we examine instead a version of evolutionary iterated prisoner's dilemma in which an agent's fitness is measured as the average score it obtains against a fixed panel of o... View full abstract»

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  • Design and Implementation of Chinese Dark Chess Programs

    Publication Year: 2015, Page(s):66 - 74
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1378 KB) | HTML iconHTML

    Chinese Dark Chess is an old and very popular game in the Chinese culture sphere. This game is a stochastic game with symmetric hidden information. This paper reviews alpha-beta search with chance nodes and proposes heuristics on Chinese Dark Chess programs. We propose an application of nondeterministic Monte Carlo Tree Search with random nodes for tackling partial observation. The proposed method... View full abstract»

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  • Learning Behaviors of and Interactions Among Objects Through Spatio–Temporal Reasoning

    Publication Year: 2015, Page(s):75 - 87
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2456 KB) | HTML iconHTML

    In this paper, we introduce an automated reasoning system for learning object behaviors and interactions through the observation of event sequences. We use an existing system to learn the models of objects and further extend it to model more complex behaviors. Furthermore, we propose a spatio-temporal reasoning based learning method for reasoning about interactions among objects. Experience gained... View full abstract»

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  • Learning-Based Procedural Content Generation

    Publication Year: 2015, Page(s):88 - 101
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1557 KB) | HTML iconHTML

    Procedural content generation (PCG) has recently become one of the hottest topics in computational intelligence and AI game research. While some substantial progress has been made in this area, there are still several challenges ranging from content evaluation to personalized content generation. In this paper, we present a novel PCG framework based on machine learning, named learning-based procedu... View full abstract»

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  • Sequential Halving Applied to Trees

    Publication Year: 2015, Page(s):102 - 105
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (560 KB) | HTML iconHTML

    Monte Carlo tree search (MCTS) is state of the art for multiple games and problems. The base algorithm currently used for MCTS is UCT. We propose an alternative MCTS algorithm: sequential halving applied to Trees (SHOT). It has multiple advantages over UCT: it spends less time in the tree, it uses less memory, it is parameter free, at equal time settings it beats UCT for a complex combinatorial ga... View full abstract»

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  • IEEE Computational Intelligence Society Information

    Publication Year: 2015, Page(s): C3
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  • IEEE Transactions on Computational Intelligence and AI in Games information for authors

    Publication Year: 2015, 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