Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)

Fuzzy Multiset Clustering for Metagame Analysis

Authors
Alexander Dockhorn, Tony Schwensfeier, Rudolf Kruse
Corresponding Author
Alexander Dockhorn
Available Online August 2019.
DOI
10.2991/eusflat-19.2019.74How to use a DOI?
Keywords
Fuzzy multisets Clustering Meta-game analysis Hearthstone
Abstract

Developing agents for automated game playing is a demanding task in the general game production cycle. Especially the involvement of frequent balance changes after the release, e.g. as they often occur in collectible card games, require constant updates of the developed agent. The game's developers need to constantly analyze and understand the current meta-game for adjusting the agent's parameters, making balance changes to the game and ultimately sustaining the satisfaction of its player base. The underlying analysis largely depends on evaluating players' play traces. Necessary adjustments to the agent's and the game's parameters are taken care of by the game's developers. This paper proposes a first step in automatically observing the current state of a collectible card game, which will assist the developers in their understanding of established deck archetypes and, therefore, speed up the update cycle. Fuzzy multisets are used for modelling decks and frequently occurring subsets of cards. We propose the definition of a (fuzzy) multiset centroid to uniquely represent the cluster and its contained decks and show that it better matches the deck archetype than the often reported deck core. The proposed clustering procedure identifies deck archetypes and takes track of its common variants in the current meta-game. We evaluate the approach by comparing the result of our clustering procedure with a hand labeled data set and show that it is able to reproduce clusters of similar quality to a labeling provided by experts.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
Series
Atlantis Studies in Uncertainty Modelling
Publication Date
August 2019
ISBN
978-94-6252-770-6
ISSN
2589-6644
DOI
10.2991/eusflat-19.2019.74How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Alexander Dockhorn
AU  - Tony Schwensfeier
AU  - Rudolf Kruse
PY  - 2019/08
DA  - 2019/08
TI  - Fuzzy Multiset Clustering for Metagame Analysis
BT  - Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
PB  - Atlantis Press
SP  - 536
EP  - 543
SN  - 2589-6644
UR  - https://doi.org/10.2991/eusflat-19.2019.74
DO  - 10.2991/eusflat-19.2019.74
ID  - Dockhorn2019/08
ER  -