Notice
There is currently an issue with the citation download feature. Learn more

IEEE Transactions on Computational Intelligence and AI in Games

Issue 4 • Dec. 2016

Filter Results

Displaying Results 1 - 17 of 17
  • Table of Contents

    Publication Year: 2016, Page(s): C1
    Request permission for commercial reuse | PDF file iconPDF (138 KB)
    Freely Available from IEEE
  • IEEE Transactions on Computational Intelligence and AI in Games

    Publication Year: 2016, Page(s): C2
    Request permission for commercial reuse | PDF file iconPDF (56 KB)
    Freely Available from IEEE
  • Guest Editorial Real-Time Strategy Games

    Publication Year: 2016, Page(s):317 - 318
    Request permission for commercial reuse | PDF file iconPDF (102 KB) | HTML iconHTML
    Freely Available from IEEE
  • Hybrid Pathfinding in StarCraft

    Publication Year: 2016, Page(s):319 - 324
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (755 KB) | HTML iconHTML

    Micromanagement is a very important aspect of real-time strategy (RTS) games. It involves moving single units or groups of units effectively on the battle field, targeting the most threatening enemy units and use the unit's special abilities when they are the most harmful for the enemy or the most beneficial for the player. Designing good micromanagement is a challenging task for AI bot developers... View full abstract»

    Open Access
  • Competitive Algorithms for Coevolving Both Game Content and AI. A Case Study: Planet Wars

    Publication Year: 2016, Page(s):325 - 337
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1311 KB) | HTML iconHTML

    The classical approach of competitive coevolution (CC) applied in games tries to exploit an arms race between coevolving populations that belong to the same species (or at least to the same biotic niche), namely strategies, rules, tracks for racing, or any other. This paper proposes the coevolution of entities belonging to different realms (namely biotic and abiotic) via a competitive approach. Mo... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multiscale Bayesian Modeling for RTS Games: An Application to StarCraft AI

    Publication Year: 2016, Page(s):338 - 350
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2302 KB) | HTML iconHTML

    This paper showcases the use of Bayesian models for real-time strategy (RTS) games AI in three distinct core components: micromanagement (units control), tactics (army moves and positions), and strategy (economy, technology, production, army types). The strength of having end-to-end probabilistic models is that distributions on specific variables can be used to interconnect different models at dif... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Evolving Effective Microbehaviors in Real-Time Strategy Games

    Publication Year: 2016, Page(s):351 - 362
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (576 KB)

    We investigate heuristic search algorithms to generate high-quality micromanagement in combat scenarios for real-time strategy (RTS) games. Macro- and micromanagement are two key aspects of RTS games. While good macro helps a player collect more resources and build more units, good micro helps a player win skirmishes and battles against equal numbers and types of opponent units or win even when ou... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Coevolving Robust Build-Order Iterative Lists for Real-Time Strategy Games

    Publication Year: 2016, Page(s):363 - 376
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (836 KB) | HTML iconHTML

    We investigate and develop a coevolutionary approach to finding strong, robust build orders for real-time strategy games. Which units to produce and the order in which to produce them is one important aspect of real-time strategy gameplay. In real-time strategy games, creating plans to address unit production problems are called “build orders.” Our research compares build orders prod... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • ghost: A Combinatorial Optimization Framework for Real-Time Problems

    Publication Year: 2016, Page(s):377 - 388
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (344 KB) | HTML iconHTML

    This paper presents GHOST, a combinatorial optimization framework that a real-time strategy (RTS) AI developer can use to model and solve any problem encoded as a constraint satisfaction/optimization problem (CSP/COP). We show a way to model three different problems as a CSP/COP, using instances from the RTS game StarCraft as test beds. Each problem belongs to a specific level of abstraction (the ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Coevolutionary CMA-ES for Knowledge-Free Learning of Game Position Evaluation

    Publication Year: 2016, Page(s):389 - 401
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1765 KB) | HTML iconHTML

    One weakness of coevolutionary algorithms observed in knowledge-free learning of strategies for adversarial games has been their poor scalability with respect to the number of parameters to learn. In this paper, we investigate to what extent this problem can be mitigated by using Covariance Matrix Adaptation Evolution Strategy, a powerful continuous optimization algorithm. In particular, we employ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Intentionality and Conflict in The Best Laid Plans Interactive Narrative Virtual Environment

    Publication Year: 2016, Page(s):402 - 411
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1811 KB) | HTML iconHTML

    In this paper, we present The Best Laid Plans, an interactive narrative adventure game, and the planning technologies used to generate and adapt its story in real time. The game leverages computational models of intentionality and conflict when controlling the non-player characters (NPCs) to ensure they act believably and introduce challenge into the automatically generated narratives. We evaluate... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Statistical Relational Learning for Game Theory

    Publication Year: 2016, Page(s):412 - 425
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1751 KB) | HTML iconHTML

    In this paper, we motivate the use of models and algorithms from the area of Statistical Relational Learning (SRL) as a framework for the description and the analysis of games. SRL combines the powerful formalism of first-order logic with the capability of probabilistic graphical models in handling uncertainty in data and representing dependencies between random variables: for this reason, SRL mod... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Introducing IEEE Collabratec

    Publication Year: 2016, Page(s): 426
    Request permission for commercial reuse | PDF file iconPDF (1924 KB)
    Freely Available from IEEE
  • AI Game Design

    Publication Year: 2016, Page(s): 427
    Request permission for commercial reuse | PDF file iconPDF (676 KB)
    Freely Available from IEEE
  • AI Serious Games

    Publication Year: 2016, Page(s): 428
    Request permission for commercial reuse | PDF file iconPDF (1288 KB)
    Freely Available from IEEE
  • IEEE Computational Intelligence Society

    Publication Year: 2016, Page(s): C3
    Request permission for commercial reuse | PDF file iconPDF (58 KB)
    Freely Available from IEEE
  • Information for Authors

    Publication Year: 2016, Page(s): C4
    Request permission for commercial reuse | PDF file iconPDF (57 KB)
    Freely Available from IEEE

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