publication . Bachelor thesis . 2016

Content evaluation of StarCraft maps using Neuroevolution

Larsson, Sebastian; Petri, Ossian;
Open Access English
  • Published: 01 Jan 2016
  • Publisher: Blekinge Tekniska Högskola, Institutionen för kreativa teknologier
  • Country: Sweden
Abstract
Context. Games are becoming larger and the amount of assets required is increasing. Game studios turn toward procedural generation to ease the load of asset creation. After the game is released the studios want to extend the longevity of their creation. One way of doing this is to open up the game for community created add-ons and assets or utilize some procedural content generation. Both community created assets and procedural generation comes with a classification problem to filter out the undesirable content. Objectives. This thesis will attempt to create a method to evaluate community-generated StarCraft maps with the help of machine learning. Methods. Manua...
Subjects
free text keywords: neural networks, NEAT, automated evaluation, StarCraft, Computer Sciences, Datavetenskap (datalogi)
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