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Game Design: Theory
Abstract: This article examines the tension in game content production between the systematic reduction of specific cases to general rules on the one hand, and the deliberate construction of unique player experiences on the other. We shall see how market and design trends are pushing games towards hybrid styles that combine these two approaches, before accusing most work in game AI of remaining too closely tied to the reduction to general rules in its commitment to strongly autonomous game agents. A quick review of related themes in sociology and psychology sets us up for the last part of the article, exploring the notion of what we call a 'situationist' game AI, capable of meeting this hybrid challenge.
Artificial Personality: A Personal Approach to AI |
Abstract: Artificial personality is a powerful conceptual framework for creating compelling artificial intelligence in most type of games. It gives direction and focus to the underlying algorithms that make up all AI, encouraging a style of play which revolves around understanding and exploiting personality archetypes such as the coward, the defender, the psycho, etc. This technique was used successfully in Bicycle� Texas Hold'em from Carbonated Games in 2006, published by MSN Games.
Creating Designer Tunable AI |
Abstract: This article describes tips and techniques for working with designers to create better AI systems and improve their utilization in-game. It covers the advantages and disadvantages of various methods for allowing designers control over AI systems, guidelines for how much to expose in scripting systems, how to organize tunable data for data driven systems, and pitfalls to avoid in implementing such systems. It also discusses how to consider designer workflow in system design and communication tips to make sure designers understand how to use these systems.
Ecological Balance in AI Design |
Abstract: This article considers the ways in which entrenched methods of game design can lead to unproductive tensions with advances in game AI technology. This issue encompasses not only methods of thinking about game design, but also styles of design documentation, and working relationships between designers and AI coders when iterating on game features. The result is not only a failure to produce useful increases in gameplay complexity. In some cases the result is actually a reduction in complexity, due to the inability of outdated design approaches to effectively control a more complex AI architecture.
Declarative AI Design for Games—Considerations for MMOGs |
Abstract: The design of behaviors in games and massively multiplayer online games (MMOGs) is based on a style of scripting that is consistent with a cinematic perspective of game design. This style is paradigmatic of how AI is conceptualized in games. This article claims that this approach is not likely to scale in the future and calls for a more declarative style of developing and conceptualizing AI. The objective of this article is to acquaint games AI developers with thoughts and techniques that form a declarative AI design.
Abstract: As gamers demand more realistic AI and more dynamic, non-linear, and interactive game worlds, traditional methods of developing AI are beginning to show their limitations in terms of salability, robustness and general fitness for purpose. Emergence and the broader "emergent approach" to game design hold great potential as an efficient tool for avoiding these limitations by allowing high-level behaviors and flexible game environments to emerge from low level building blocks without the need for any hard-coded or scripted behaviors. Our goals in this article are to both demonstrate this case, and to explain in practical terms how emergence can be captured by the game designer.
Fun Game AI Design for Beginners |
Abstract: This article is meant to provide food for thought on a number of issues involving AI design. Creating predictable, understandable and consistent AI that doesn't beat the player all the time is no easy task. The AI programmer must make sure that the AI gives the player time to react, doesn't have cheap shots against the player and isn't too simple or too complex. The AI is meant to enrich the player's enjoyment of the game, not to frustrate them, so these rules are important to consider in order to create an enjoyable experience for the player. If you are developing a game AI the best thing you can do (besides considering these rules) is to come up with your own rules from games that you enjoy playing.
World Building: From Paper to Polygons |
Meaningful Game Mechanics |
Pros and Cons of Hit Point Systems |
Alternatives to Numbers in Game Design Models |
Increasing Challenge without Frustrating Players |
Nine Trade-Offs of Game Design |
Adapting Licensed Properties |
Warning Signs of Faulty Game Design |
Virtual Worlds: Why People Play |
The Three Thirties of MMP Game Design |
Balancing Gameplay for Thousands of Your Harshest Critics |
Power by the People: User-Creation in Online Games |
Games Within Games: Graph Theory for Designers-Part 1 |
Worlds Within Worlds: Graph Theory for Designers-Part 2 |
Guild Management Tools for a Successful MMP Game |
A Stock Exchange-Inspired Commerce System |
Alternatives to the Character Grind |
Great in Theory: Examining the Gap Between System Design Theory and Reality |
Toontown Online: Building Massively Multiplayer Games for the Masses |
Everybody Needs Somebody: Practical Advice for Encouraging Cooperative Play in Online Virtual Worlds |
Game Balance for Massively Multiplayer Games |
Game Balance and AI Using Payoff Matrices |
Describing Game Behavior with Use Cases |
Using a Hit Point to Coin Conversion Factor |
Designing Massively Multiplayer Games for Narrative Investment |
Customer Support and Player Reputation: It�s All About Trust |
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