Deck Building in Collectible Card Games using Genetic Algorithms: A Case Study of Legends of Code and Magic

Ya Ju Yang, Tsung Su Yeh, Tsung Che Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Collectible card games (CCGs) are a kind of game in which players use a variety of cards to achieve the goal of game, for example, defeating the opponent. To play a game, players need to build a card deck, which consists of specified number of cards; only cards in the deck can be used in the game. Deck building is an important part in playing CCGs. This paper addresses deck building in a recently released CCG, Legends of Code and Magic. Our strategy is to evaluate cards by some scoring functions and then select cards into the deck accordingly. We adopt three types of scoring functions and use genetic algorithms (GA) to set proper values of parameters in the scoring functions. We checked the performance of the three versions of deck-building GAs against existing agents and found that scoring by card attributes is effective. We also analyzed the decks built by these algorithms and discussed their pros and cons.

Original languageEnglish
Title of host publication2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728190488
DOIs
Publication statusPublished - 2021
Event2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Orlando, United States
Duration: 2021 Dec 52021 Dec 7

Publication series

Name2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings

Conference

Conference2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021
Country/TerritoryUnited States
CityOrlando
Period2021/12/052021/12/07

Keywords

  • Collectible card game
  • Deck building
  • Genetic algorithm
  • Legends of Code and Magic

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Decision Sciences (miscellaneous)
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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