Abstract
Mimicry and play are fundamental learning processes by which
individuals can acquire behaviours, skills and norms. In this paper we
utilise these two processes to create new game characters by
mimicking and learning from actual human players. We present our
approach towards aiding the design process of game characters through
the use of genetic programming. The current state of the art in game
character design relies heavily on human designers to manually create
and edit scripts and rules for game characters. Computational
creativity approaches this issue with fully autonomous character
generators, replacing most of the design process using black box
solutions such as neural networks. Our GP approach to this problem not only mimics actual human play but creates character controllers which can be further authored and developed by a designer.
This keeps the designer in the loop while reducing repetitive labour. Our system also provides insights into how players express themselves
in games and into deriving appropriate models for representing those insights. We present our framework and preliminary results supporting
our claim.
individuals can acquire behaviours, skills and norms. In this paper we
utilise these two processes to create new game characters by
mimicking and learning from actual human players. We present our
approach towards aiding the design process of game characters through
the use of genetic programming. The current state of the art in game
character design relies heavily on human designers to manually create
and edit scripts and rules for game characters. Computational
creativity approaches this issue with fully autonomous character
generators, replacing most of the design process using black box
solutions such as neural networks. Our GP approach to this problem not only mimics actual human play but creates character controllers which can be further authored and developed by a designer.
This keeps the designer in the loop while reducing repetitive labour. Our system also provides insights into how players express themselves
in games and into deriving appropriate models for representing those insights. We present our framework and preliminary results supporting
our claim.
Original language | English |
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Number of pages | 6 |
Publication status | Published - 8 Sept 2015 |
Event | 17th Portuguese Conference on Artificial Intelligence (EPIA-2015) - University of Coimbra, Coimbra, Portugal Duration: 8 Sept 2015 → 11 Sept 2015 |
Conference
Conference | 17th Portuguese Conference on Artificial Intelligence (EPIA-2015) |
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Country/Territory | Portugal |
City | Coimbra |
Period | 8/09/15 → 11/09/15 |
Keywords
- agent design
- games
- genetic programming
- machine learning