Introduction to Game AI: Core Concepts u0026 History Quiz Quiz

Explore essential concepts and the historical development of artificial intelligence in games with this focused quiz. Assess your grasp of foundational Game AI techniques, key milestones, and their practical applications in virtual environments.

1. Defining Game AI

   Which of the following best describes the core purpose of artificial intelligence in video games?

   1. To improve network connectivity between remote players
   2. To encrypt players’ personal data for security
   3. To create believable, adaptive behaviors for non-player characters (NPCs)
   4. To generate realistic graphics and visual effects

   Explanation: The main role of Game AI is to design behaviors that make NPCs seem intelligent and capable of responding dynamically to player actions. Improving network connectivity is related to online infrastructure, not AI logic. Graphics and visual effects focus on visuals, while data encryption is a security concern, not directly related to AI behavior in games.

2. AI Technique Origins

   Which early AI technique, often used in classic arcade games like Pac-Man, involves decision trees for non-player actions?

   1. Genetic Algorithms
   2. Finite State Machines
   3. Neural Networks
   4. Pathtracing

   Explanation: Finite State Machines (FSMs) represent AI logic as different states, with transitions based on input or conditions—commonly used for classic game characters. Neural networks and genetic algorithms are more advanced and compute-heavy, emerging later. Pathtracing is unrelated to AI, being a rendering technique for lighting and visuals.

3. Key Milestone in Game AI History

   Which event marked a significant milestone in public awareness of artificial intelligence’s potential in gaming, featuring a computer program that defeated a human champion?

   1. An online match hosting thousands of players simultaneously
   2. A game introducing procedurally generated levels
   3. A program defeating a world chess champion
   4. A computer rendering 3D graphics in real time

   Explanation: The world took notice when a computer program beat a top chess player, showcasing AI’s strategic planning and decision-making power. While rendering 3D graphics is technologically impressive, it is unrelated to AI. Procedural generation involves algorithms for content creation, not intelligence. Massive online matches highlight scalability, not AI capabilities.

4. Pathfinding Algorithms in Games

   Which algorithm is most commonly used in video games for efficient shortest-path navigation of NPCs around obstacles, such as guiding a guard to chase a player?

   1. A* (A-star) algorithm
   2. Bitmasking
   3. Bubble Sort
   4. Gradient Descent

   Explanation: A* (A-star) is a well-known pathfinding algorithm enabling NPCs to efficiently navigate around barriers and reach goals, a staple in game development. Bubble Sort is solely a sorting method, and Gradient Descent is used for optimization in machine learning, not navigation. Bitmasking is a data representation technique, not related to pathfinding.

5. Behavior Trees in Modern Game AI

   How do behavior trees, an AI architecture used in many modern games, improve upon simple state machines when controlling complex NPC behavior?

   1. They randomly assign actions each game loop
   2. They require less memory but sacrifice behavior complexity
   3. They disable any form of reactive action adaptation
   4. They allow hierarchical, flexible action selection and decision making

   Explanation: Behavior trees organize decisions hierarchically, making NPC behaviors easier to structure, manage, and expand, especially for complex or layered actions. Randomly assigning actions does not help create intelligent agents. Using less memory at the cost of complexity is not a key feature, and disabling adaptability contradicts the flexibility that behavior trees specifically provide.