Abstract
This paper presents a novel approach to procedural generation of urban maps for First Person Shooter (FPS) games. A multi-agent evolutionary system is employed to place streets, buildings and other items inside the Unity3D game engine, resulting in playable video game levels. A computational agent is trained using machine learning techniques to capture the intent of the game designer as part of the multi-agent system, and to enable a semi-automated aesthetic selection for the underlying genetic algorithm.
Original language | English |
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Title of host publication | Interactive Entertainment 2016, 2-5 February, Canberra, Australia |
Subtitle of host publication | [part of the] Australasian Computer Science Week (ACSW 2016) [proceedings] |
Place of Publication | New York, NY |
Publisher | Association for Computing Machinery (ACM) |
Number of pages | 5 |
ISBN (Electronic) | 9781450340427 |
DOIs | |
Publication status | Published - 1 Feb 2016 |
Externally published | Yes |
Event | Interactive Entertainment 2016 - Canberra, Australia Duration: 2 Feb 2016 → 5 Feb 2016 http://ieconference.org/ie2016/ |
Conference
Conference | Interactive Entertainment 2016 |
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Abbreviated title | IE 2016 |
Country | Australia |
City | Canberra |
Period | 2/02/16 → 5/02/16 |
Internet address |
Keywords
- Agents
- Artificial intelligence
- Computer games
- First person shooter, urban environment
- Genetic algorithm
- Procedural environment
- Unity