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AI Wisdom book series is going OUT OF PRINT
Used copies of AI Game Programming Wisdom 4 are selling for $440.00 on Amazon. There are a couple new copies of the first volume from Amazon resellers at a reasonable price ($54.73). Volumes 2 and 3 are still available, but since new books won't be printed, they will soon be just as scarce.

The whole series will soon be out of print - get your copies
before they are gone:

  • $54.73 (8 new books left from resellers) AI Game Programming Wisdom 1
  • $39.96 (43% off) AI Game Programming Wisdom 2
  • $39.96 (43% off) AI Game Programming Wisdom 3
  • $440.00 (USED PRICE - out of print premium) AI Game Programming Wisdom 4

  • Please don't contact me about AI Game Programming Wisdom 4 books. I don't have any to offer.


    Game AI: Genre - RPG and Adventure


    Stop Getting Side-Tracked by Side-Quests

    Curtis Onuczko, Duane Szafron, and Jonathan Schaeffer (University of Alberta)
    AI Game Programming Wisdom 4
    Abstract: Computer role-playing games often contain a complex main story-line and a series of smaller optional independent mini-stories called side-quests. Side-quests create an open world feeling, provide rewards and experience to the player for exploring optional game content, and build upon the background of the main story without affecting it. The more side-quests you add to your game, the richer the game experience will be for the player. However, more side-quests means more work generating content. This article discusses a Side-QUEst GENerator (SQUEGE) tool that will minimize the amount of time and effort needed to add side-quests to a game story. By using the patterns that exist in stories, SQUEGE intelligently provides an interesting and meaningful structure to the side-quests it produces. The result is a set of automatically generated side-quest outlines. The outlines can then be adapted, giving the game author authorial control over the side-quests generated. Finally, a programmer can use the adapted outlines to create the necessary game scripts in a straightforward manner. This process makes the creation of a large number of side-quests both easy and efficient, saving precious time and resources. The generator is easily extendable to allow for the addition of new patterns.

    Spoken Dialogue Systems

    Hugo Pinto and Roberta Catizone (University of Sheffield)
    AI Game Programming Wisdom 4
    Abstract: This article provides an overview of modern dialog systems. We start by presenting the issues of voice recognition, language processing, dialog management, language generation and speech synthesis. Next, we analyze two robust speech-based interactive systems, NICE and TRIPS, examining how they solved each of the issues involved in spoken dialog processing. Finally, we examine the particulars of the game domain and provide suggestions on how to approach it, with illustrations from the case studies.

    Implementing Story-Driven Games with the Aid of Dynamical Policy Models

    Fabio Zambetta (School of Computer Science & IT, RMIT University)
    AI Game Programming Wisdom 4
    Abstract: In this article we introduce a mathematical model of conflict that enhances Richardson's model of Arms Race accounting for interactive scenarios, such as the ones provided by Computer Role Playing Games. Accordingly, an HCP (Hybrid Control Process) is devised that can be combined with fuzzy rules to provide help in modeling non-linear interactive stories. The model presented here can be adopted by game AI programmers to better support the game designers' job, and to provide an interesting and unconventional type of gameplay to players. We also introduce the multi-disciplinary project Two Familes: A Tale of New Florence, which will illustrate the applications of our model.

    Individualized NPC Attitudes with Social Networks

    Christian J. Darken (The MOVES Institute), John D. Kelly (U.S. Navy)
    AI Game Programming Wisdom 4
    Abstract: This article introduces a method for largely automating NPC changes in attitude due to a player action. The method resolves the conflicting loyalties of the NPC's to produce a single number per NPC that can be used to update the NPC's feelings toward the player and drive future player-NPC interactions. The mechanics of the method are based on a constrained linear system, so it is computationally efficient, requiring only a single matrix multiplication in many applications.

    Dialogue Managers

    Hugo Pinto (University of Sheffield)
    AI Game Programming Wisdom 4
    Abstract: This article presents the main techniques and paradigms of dialog management, with references to games, industrial applications and academic research. We cover dialog managers based on stacks, finite-state machines, frames, inference-engines and planners. For each technique, we point its strengths, applicability and issues when integrating into a broader dialog system in a game setting.

    Player Modeling for Interactive Storytelling: A Practical Approach

    David Thue, Vadim Bulitko, and Marcia Spetch (University of Alberta)
    AI Game Programming Wisdom 4
    Abstract: As computer graphics becomes less of a differentiator in the video game market, many developers are turning to AI and storytelling to ensure that their title stands out from the rest. To date, these have been approached as separate, incompatible tasks; AI engineers feel shackled by the constraints imposed by a story, and the story's authors fear the day that an AI character grabs their leading actor and throws him off a bridge. In this article, we attempt to set aside these differences, bringing AI engineers together with authors through a key intermediary: a player model. Following an overview of the present state of storytelling in commercial games, we present PaSSAGE (Player-Specific Stories via Automatically Generated Events), a storytelling AI that both learns and uses a player model to dynamically adapt a game's story. By combining the knowledge and expertise of authors with a learned player model, PaSSAGE automatically creates engaging and personalized stories that are adapted to appeal to each individual player.

    Otello: A Next-Generation Reputation System for Humans and NPCs

    Michael Sellers (Online Alchemy)
    PDF link, Artificial Intelligence and Interactive Digital Entertainment (AIIDE)
    Abstract: This paper introduces Online Alchemy’s Otello technology as a way to enable reputational capabilities beyond any found in games or other online social contexts today. This technology allows participants to quickly and easily assess another’s reputation in ways meaningful to them, and enables individuals -- both players and non-player characters (NPCs) -- to contribute to an individual’s reputation in unique and novel ways. Otello also enables new forms of 'relational gameplay' that feature social management, effectively an extension of resource management into the social realm. The player’s actions and opinions affect others, including how they see the player, and how ideas and opinions propagate through a population.

    Opinion Systems

    Adam Russell (Lionhead Studios)
    AI Game Programming Wisdom 3
    Abstract: Modeling the formation and effect of opinions about the player character in a simulated social environment is a difficult problem for game AI, but one increasingly worth tackling. This article discusses some of the wisdom gained during the construction of perhaps the most complex opinion system ever seen in a commercial game, that of Lionhead Studios' Fable.

    Ant Colony Organization for MMORPG and RTS Creature Resource Gathering

    Jason Dunn (H2Code)
    AI Game Programming Wisdom 3
    Abstract: This article provides details about the implementation of ant colonies for pathfinding in massively multiplayer and real-time strategy games. Details include the effects of pheromones and individual ant behavior, as well as what variables to focus on when adapting the provided source code. Readers are taught how to control the elasticity of path seeking and path reinforcement.

    Fast Target Ranking Using an Artificial Potential Field

    Markus Breyer (Factor 5)
    Game Programming Gems 5

    Using Lanchester Attrition Models to Predict the Results of Combat

    John Bolton (Page 44 Studios)
    Game Programming Gems 5

    Building a Massively Multiplayer Game Simulation Framework, Part 2: Behavioral Modeling

    Thor Alexander (Hard Coded Games)
    Massively Multiplayer Game Development

    Level-Of-Detail AI for a Large Role-Playing Game

    Mark Brockington (BioWare)
    AI Game Programming Wisdom
    Abstract: With thousands of objects demanding AI time slices in Neverwinter Nights, it would be difficult to satisfy all creatures and maintain a playable frame rate. The level-of-detail AI schemes used allowed the game to achieve the perception of thousands of actors thinking simultaneously. The article discusses how to subdivide your game objects into categories, and how certain time-intensive actions (such as pathfinding and combat) can be reduced to make more efficient use of the time available to AI.

    A Dynamic Reputation System Based on Event Knowledge

    Greg Alt (Surreal Software), Kristin King
    AI Game Programming Wisdom
    Abstract: This article describes a non-player character (NPC) reputation system (a mechanism for dynamically managing NPCs' opinions of each other and of the player in order to influence the NPCs' actions). Most existing reputation systems manage NPCs' opinions globally. The reputation system this article describes instead changes a specific NPC's opinions only if the NPC has direct or indirect knowledge of events that trigger a change. The article describes the data structures required for the reputation system, the way they work together to make the complete system, and the way the system fits into the overall design of NPC behavior.

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