<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The Multiplayer Online Battle Arena (MOBA) game is a popular type for its competition between players. Due to the high complexity, balance is the most important factor to secure a fair competitive environment. The common way to achieve dynamic data balance is by constant updates. The traditional method of finding unbalanced factors is mostly based on professional tournaments, a small minority of all the games and not real time. We develop an evaluation system for the DOTA2 based on big data with clustering analysis, neural networks, and a small-scale data collection as a sample. We then provide an ideal matching system based on the Elo rating system and an evaluation system to encourage players to try more different heroes for a diversified game environment and more data supply, which makes for a virtuous circle in the evaluation system.</p></abstract>

The Multiplayer Online Battle Arena (MOBA) game is a popular type for its competition between players. Due to the high complexity, balance is the most important factor to secure a fair competitive environment. The common way to achieve dynamic data balance is by constant updates. The traditional method of finding unbalanced factors is mostly based on professional tournaments, a small minority of all the games and not real time. We develop an evaluation system for the DOTA2 based on big data with clustering analysis, neural networks, and a small-scale data collection as a sample. We then provide an ideal matching system based on the Elo rating system and an evaluation system to encourage players to try more different heroes for a diversified game environment and more data supply, which makes for a virtuous circle in the evaluation system.

Improved balance in multiplayer online battle arena games

Acta Universitatis Sapientiae, Informatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Improved balance in multiplayer online battle arena games"}

The Multiplayer Online Battle Arena (MOBA) game is a popular type for its competition between players. Due to the high complexity, balance is the most...

Improved balance in multiplayer online battle arena games

Online veröffentlicht: 29. Jan. 2021

Seitenbereich: 183 - 204

Eingereicht: 18. Mai 2020

Akzeptiert: 15. Sept. 2020

DOI: https://doi.org/10.2478/ausi-2020-0011

Schlüsselwörter
mupliplayer online battle arena game, game balance, matching system, clustering, neural network

© 2020 Chailong Huang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Improved balance in multiplayer online battle arena games

Online veröffentlicht: 29. Jan. 2021

Seitenbereich: 183 - 204

Eingereicht: 18. Mai 2020

Akzeptiert: 15. Sept. 2020

DOI: https://doi.org/10.2478/ausi-2020-0011

Schlüsselwörtermupliplayer online battle arena game, game balance, matching system, clustering, neural network

© 2020 Chailong Huang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
mupliplayer online battle arena game, game balance, matching system, clustering, neural network