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https://doi.org/10.1109/cig.20...
Article . 2016 . Peer-reviewed
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DBLP
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Towards the automatic optimisation of procedural content generators

Authors: Michael Cook 0001; Jeremy Gow; Simon Colton;

Towards the automatic optimisation of procedural content generators

Abstract

Procedural generation is important to modern game development as both an artistic implement and an engineering tool. However, developing procedural generators and understand- ing how they work are both difficult tasks, and even more so for novice developers. In this paper we describe Danesh, a tool to help in analysing, changing and exploring procedural content generators. In particular, we describe several features in Danesh which help a user optimise their procedural generator towards a certain kind of output by automatically changing parameters and evaluating the effect it has on the generator. We compare different approaches to these tasks and describe our future intentions for Danesh’s automated features.

Keywords

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Top 10%
Average
Green