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  1. KEEP
  2. Theses and Dissertations
  3. Barrett, The Honors College Thesis/Creative Project Collection
  4. Behavior Trees + Finite State Machines: A Hybrid Game AI Framework
  5. Full metadata

Behavior Trees + Finite State Machines: A Hybrid Game AI Framework

Full metadata

Description

One of the core components of many video games is their artificial intelligence. Through AI, a game can tell stories, generate challenges, and create encounters for the player to overcome. Even though AI has continued to advance through the implementation of neural networks and machine learning, game AI tends to implement a series of states or decisions instead to give the illusion of intelligence. Despite this limitation, games can still generate a wide range of experiences for the player. The Hybrid Game AI Framework is an AI system that combines the benefits of two commonly used approaches to developing game AI: Behavior Trees and Finite State Machines. Developed in the Unity Game Engine and the C# programming language, this AI Framework represents the research that went into studying modern approaches to game AI and my own attempt at implementing the techniques learned. Object-oriented programming concepts such as inheritance, abstraction, and low coupling are utilized with the intent to create game AI that's easy to implement and expand upon. The final goal was to create a flexible yet structured AI data structure while also minimizing drawbacks by combining Behavior Trees and Finite State Machines.

Date Created
2018-05
Contributors
  • Ramirez Cordero, Erick Alberto (Author)
  • Kobayashi, Yoshihiro (Thesis director)
  • Nelson, Brian (Committee member)
  • Computer Science and Engineering Program (Contributor)
  • Computing and Informatics Program (Contributor)
  • Barrett, The Honors College (Contributor)
Topical Subject
  • Computer Science
  • Computer Gaming
  • Game Ai
  • artificial intelligence
  • Object-Oriented Programming
  • Unity Game Engine
  • Behavior Trees
  • Finite State Machines
Extent
44 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Barrett, The Honors College Thesis/Creative Project Collection
Series
Academic Year 2017-2018
Handle
https://hdl.handle.net/2286/R.I.48032
Level of coding
minimal
Cataloging Standards
asu1
System Created
  • 2018-04-20 12:12:08
System Modified
  • 2021-08-11 04:09:57
  •     
  • 1 year 7 months ago
Additional Formats
  • OAI Dublin Core
  • MODS XML

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