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Team Composition in PES2018 Using Submodular Function Optimization
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DOI：10.1109/ACCESS.2019.2919447.png)
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摘要
En 中文
With the development of computer game technologies, gameplay becomes very realistic in many sports games, therefore providing appealing play experience to game players. To get the victory in a football pitch, the team composition is pretty important. There is little research on the automatic team composition in sports games particularly in a popular game of Pro Evolution Soccer (PES). In this paper, we consider the team composition as one team player recommendation problem since a team is composed of several players in a game. Subsequently, we aim to recommend a list of sufficiently good football players to game players. We convert the team player recommendation into one optimization problem and resort to the greedy algorithm-based solutions.We propose a coverage function that quantifies the degree of soccer skills to be covered by the selected players. In addition, we prove the submodularity of the coverage function and improve a greedy algorithm to solve the function optimization problem.We demonstrate the performance of our techniques in PES2018.
Keyword:
Team composition
recommender
submodularity
PES2018
AI总结
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期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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