Analysis on the Optimal Moves Prediction for Hearthstone

DOI

10.2991/assehr.k.220504.144How to use a DOI?

Keywords

hearthstone; card game; deck tracking; game theory; games

Abstract

Even though there are many different game modes in Hearthstone, the main idea is still to combat between players. In classic mode, each player will have its own preconstructed decks and choose one of them after the banning phase. In addition, Battleground is another game mode that contains 8 players, each player will choose a hero to play with. In the game, each round it’s a 1v1 combat between 2 players. So in general, Hearthstone is a digital card game in which 2 players compete with each other. Such tournaments measure players’ skills and are exciting for viewers, but can take place in a variety of match formats which fans claim drastically affect the competitiveness and viewer engagement. In battleground mode, even though each hero has its own abilities, there should be an optimal way to play each round in order to maximize the player’s winning rate. The purpose of this paper is to build a program that can automatically help player make the most optimal move. The idea of this comes from HsReplay, the author uses its database. Even though the whole program is still developing and improving, it contains some basic functions for some specific heroes. This paper provides some references for software development to help players make the optimal moves under certain fixed conditions so that they can win the game eventually.

Copyright

© 2022 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

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TY  - CONF
AU  - Haoxuan Wei
PY  - 2022
DA  - 2022/06/01
TI  - Analysis on the Optimal Moves Prediction for Hearthstone
BT  - Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)
PB  - Atlantis Press
SP  - 785
EP  - 790
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220504.144
DO  - 10.2991/assehr.k.220504.144
ID  - Wei2022
ER  -