Adaptive puzzle generation for computational thinking

Marco Scirea*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper describes a system to generate puzzles with a difficulty degree that adapts to the player. The puzzle is designed with the objective of being used by young pupils, and it is mainly a planning/sequencing task, which is considered one of the aspects of computational thinking. The system is powered by a constrained multi-objective algorithm (NSFI-2Pop) – which evolves the sequences of actions necessary to solve the puzzle – combined with a stochastic algorithm that translates the sequences in playable levels. We also present a pilot evaluation of the system, which seems to indicate that the levels presented to the player are perceived as having an increasing difficulty.

Original languageEnglish
Title of host publicationHCI in Games - 2nd International Conference, HCI-Games 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Proceedings
EditorsXiaowen Fang
PublisherSpringer
Publication date2020
Pages471-485
ISBN (Print)978-3-030-50163-1
ISBN (Electronic)978-3-030-50164-8
DOIs
Publication statusPublished - 2020
Event2nd International Conference on HCI in Games, HCI-Games 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020 - Copenhagen, Denmark
Duration: 19. Jul 202024. Jul 2020

Conference

Conference2nd International Conference on HCI in Games, HCI-Games 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020
CountryDenmark
CityCopenhagen
Period19/07/202024/07/2020
SeriesLecture Notes in Computer Science
Volume12211
ISSN0302-9743

Keywords

  • Computational thinking
  • Evolutionary algorithms
  • Procedural content generation

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