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Computational Intelligence and AI in Games, IEEE Transactions on

Issue 2 • Date June 2010

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Displaying Results 1 - 11 of 11
  • Table of contents

    Publication Year: 2010 , Page(s): C1
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  • IEEE Transactions on Computational Intelligence and AI in Games publication information

    Publication Year: 2010 , Page(s): C2
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  • Cinematic Visual Discourse: Representation, Generation, and Evaluation

    Publication Year: 2010 , Page(s): 69 - 81
    Cited by:  Papers (1)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1039 KB) |  | HTML iconHTML  

    In this paper, we present the design, implementation, and evaluation of an end-to-end camera planning system called Darshak. Darshak automatically constructs cinematic narrative discourse of a given story in a 3-D virtual environment. It utilizes a hierarchical partial-order causal link (POCL) planning algorithm to generate narrative plans that contain story events and camera directives for filming them. Dramatic situation patterns, commonly used by writers of fictional narratives, are formalized as communicative plan operators that provide a basis for structuring the cinematic content of the story's visualization. The dramatic patterns are realized through abstract communicative operators that represent operations on a viewer's beliefs about the story and its telling. Camera shot compositions and transitions are defined in this plan-based framework as execution primitives. Darshak's performance is evaluated through a novel user study based on techniques used to evaluate existing cognitive models of narrative comprehension. Initial study reveals significant effect of the choice of visualization strategies on measured viewer comprehension. It further shows significant effect of Darshak's choice of visualization strategy on comprehension. View full abstract»

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  • Towards Intelligent Team Composition and Maneuvering in Real-Time Strategy Games

    Publication Year: 2010 , Page(s): 82 - 98
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2554 KB) |  | HTML iconHTML  

    Players of real-time strategy (RTS) games are often annoyed by the inability of the game AI to select and move teams of units in a natural way. Units travel and battle separately, resulting in huge losses and the AI looking unintelligent, as can the choice of units sent to counteract the opponents. Players are affected as well as computer commanded factions because they cannot micromanage all team related issues. We suggest improving AI behavior by combining well-known computational intelligence techniques applied in an original way. Team composition for battling spatially distributed opponent groups is supported by a learning self-organizing map (SOM) that relies on an evolutionary algorithm (EA) to adapt it to the game. Different abilities of unit types are thus employed in a near-optimal way, reminiscent of human ad hoc decisions. Team movement is greatly enhanced by flocking and influence map-based path finding, leading to a more natural behavior by preserving individual motion types. The team decision to either attack or avoid a group of enemy units is easily parametrizable, incorporating team characteristics from fearful to daredevil. We demonstrate that these two approaches work well separately, but also that they go together naturally, thereby leading to an improved and flexible group behavior. View full abstract»

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  • Progress Through Uncertainty in Some Kriegspiel Endings

    Publication Year: 2010 , Page(s): 99 - 110
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1264 KB) |  | HTML iconHTML  

    Kriegspiel is a wargame based on the rules of Chess. In fact, the only difference between Kriegspiel and Chess is that each player does not know his opponent's moves: the two players use different boards. A player only knows the position of his own pieces, while his opponent's pieces are invisible. A referee maintains the full state of the game on a third board. He answers a player's move attempt with information on its outcome, such as checks or piece captures. The referee also rejects illegal moves, forcing the player to try again. In this case, the player can exploit the negative information he received from the referee. As Kriegspiel has a very large state space and highly dynamic uncertainty, it is a very hard game for computers to play. In this paper, we focus on the simpler, but still difficult, task of playing the endgame. While manual algorithms have been developed to checkmate the lone King in various scenarios, they are often hard to translate into code, partially or ambiguously defined, and quite inefficient in the number of moves to mate. We describe a search algorithm for exploring the Kriegspiel endgames, and provide relatively simple evaluation functions able to progress through uncertainty. We show that our algorithm achieves quick checkmate in the vast majority of situations and significantly outperforms existing manual methods. View full abstract»

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  • Controlled Procedural Terrain Generation Using Software Agents

    Publication Year: 2010 , Page(s): 111 - 119
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (640 KB) |  | HTML iconHTML  

    Procedural terrain generation is used to create landforms for applications such as computer games and flight simulators. While most of the existing work has concentrated on algorithms that generate terrain without input from the user, we explore a more controllable system that uses intelligent agents to generate terrain elevation heightmaps according to designer-defined constraints. This allows the designer to create procedural terrain that has specific properties. View full abstract»

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  • The Design of Puzzle Selection Strategies for ESP-Like GWAP Systems

    Publication Year: 2010 , Page(s): 120 - 130
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (549 KB) |  | HTML iconHTML  

    The “games with a purpose” (GWAP) genre is a type of “human computation” that outsources certain steps of the computational process to humans. Although most GWAP studies focus on the design and analysis of GWAP systems, a systematic and thorough evaluation of existing systems is lacking. We address the issue in this paper. Taking the ESP game as an example, we propose a metric, called system utility, for evaluating the performance of GWAP systems, and use analysis to study the properties of the ESP game. We argue that GWAP systems should be designed and played with strategies. To this end, based on our analysis, we implement an optimal puzzle selection strategy (OPSA) to improve GWAP systems. Using a comprehensive set of simulations, we show that the proposed OPSA approach can improve the system utility of the ESP game significantly. In addition, we implement a quasi ESP game, called ESP Lite, which embeds three puzzle selection algorithms transparently and records the complete game trace for evaluation and further research. During a one-month experiment, we have investigated the inner properties of the three strategies in real-world GWAP systems, and verified that the OPSA scheme achieves the best system utility for the ESP game. The results of this study demonstrate that GWAP systems are more efficient if they are designed and played with strategies. View full abstract»

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  • The 2009 Simulated Car Racing Championship

    Publication Year: 2010 , Page(s): 131 - 147
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1596 KB) |  | HTML iconHTML  

    In this paper, we overview the 2009 Simulated Car Racing Championship-an event comprising three competitions held in association with the 2009 IEEE Congress on Evolutionary Computation (CEC), the 2009 ACM Genetic and Evolutionary Computation Conference (GECCO), and the 2009 IEEE Symposium on Computational Intelligence and Games (CIG). First, we describe the competition regulations and the software framework. Then, the five best teams describe the methods of computational intelligence they used to develop their drivers and the lessons they learned from the participation in the championship. The organizers provide short summaries of the other competitors. Finally, we summarize the championship results, followed by a discussion about what the organizers learned about 1) the development of high-performing car racing controllers and 2) the organization of scientific competitions. View full abstract»

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  • Call for Participation - 2010 IEEE Conference on Computational Intelligence and Games (CIG)

    Publication Year: 2010 , Page(s): 148
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  • IEEE Computational Intelligence Society Information

    Publication Year: 2010 , Page(s): C3
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  • IEEE Transactions on Computational Intelligence and AI in Games Information for authors

    Publication Year: 2010 , 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

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Editor-in-Chief
Graham Kendall