Artificial intelligence (AI) increases the immersion that players can have while playing games. Modern game engines, a middleware software used to create games, implement simple AI behaviors that developers can use. Advanced AI behaviors must be implemented manually by game developers, which decreases the likelihood of game developers using advanced AI due to development overhead.
A custom game engine and custom AI architecture that handled deep reinforcement learning was designed and implemented. Snake was created using the custom game engine to test the feasibility of natively implementing an AI architecture into a game engine. A snake agent was successfully trained using the AI architecture, but the learned behavior was suboptimal. Although the learned behavior was suboptimal, the AI architecture was successfully implemented into a custom game engine because a behavior was successfully learned.
| Identifer | oai:union.ndltd.org:ETSU/oai:dc.etsu.edu:honors-1837 |
| Date | 01 December 2021 |
| Creators | Kincer, Austin |
| Publisher | Digital Commons @ East Tennessee State University |
| Source Sets | East Tennessee State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Undergraduate Honors Theses |
| Rights | Copyright by the authors., http://creativecommons.org/licenses/by-nc-nd/3.0/ |
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