Incremental inductive learning of answer set programs for maps generation problems

Julio Christian Young, Ari Saptawijaya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In game development, Procedural Content Generation is an approach that replaces the designer's task in creating contents of games, e.g., game maps. We introduce an incremental learning process that utilizes Inductive Learning (IL) of Answer Set Programs (ASP) to automate solving maps generation problems rather than to explicitly specify the characteristics of the maps. In an incremental learning process, a complex learning task is divided into a sequence of learning iterations, where each iteration consists of a set of smaller learning tasks to learn a set of rules. In order to speed up the learning process, each task in the same iteration is solved asynchronously. Our experiments show that IL of ASP successfully learns an answer set program. That is, it provides a set of rules for generating a collection of game maps that possess the same characteristics as the maps referred in the learning scenario.

Original languageEnglish
Title of host publication2019 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages483-488
Number of pages6
ISBN (Electronic)9781728152929
DOIs
Publication statusPublished - Oct 2019
Event11th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2019 - Bali, Indonesia
Duration: 12 Oct 201913 Oct 2019

Publication series

Name2019 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2019

Conference

Conference11th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2019
CountryIndonesia
CityBali
Period12/10/1913/10/19

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