Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/29487
Title: | Neuroevolutionary constrained optimization for content creation |
Authors: | Liapis, Antonios Yannakakis, Georgios N. Togelius, Julian |
Keywords: | Evolutionary computation Neural networks (Computer science) Level design (Computer science) |
Issue Date: | 2011 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Citation: | Liapis, A., Yannakakis, G. N., & Togelius, J. (2011). Neuroevolutionary constrained optimization for content creation. IEEE Conference on Computational Intelligence and Games (CIG), 2011. Seoul. 71-78. |
Abstract: | This paper presents a constraint-based procedural content generation (PCG) framework used for the creation of novel and high-performing content. Specifically, we examine the efficiency of the framework for the creation of spaceship design (hull shape and spaceship attributes such as weapon and thruster types and topologies) independently of game physics and steering strategies. According to the proposed framework, the designer picks a set of requirements for the spaceship that a constrained optimizer attempts to satisfy. The constraint satisfaction approach followed is based on neuroevolution; Compositional Pattern-Producing Networks (CPPNs) which represent the spaceship’s design are trained via a constraintbased evolutionary algorithm. Results obtained in a number of evolutionary runs using a set of constraints and objectives show that the generated spaceships perform well in movement, combat and survival tasks and are also visually appealing. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/29487 |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Neuroevolutionary_constrained_optimization_for_content_creation_2011.pdf | 1.11 MB | Adobe PDF | View/Open |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.