基于战场热点图的MOBA类游戏战术分析研究

Tactical Analysis of MOBA Games Based on Hotspot Map of Battlefield

随着电子竞技产业不断发展,除了经验、天赋、技巧等决胜因素外,数据分析对MOBA游戏的胜负手影响越来越大。针对某些MOBA类游戏无法直接通过接口获得准确数据的问题,提出根据官方提供的热点图来对核心人物的位置数据进行预处理,利用原型聚类算法思想的PNN(Probabilistic Nearest Neighbor)算法对热点图进行战术分析,最后以概率的形式导出战术:对战方核心人物去往战场核心点的移动概率。本算法加入了加权距离以改善KNN利用欧氏距离计算样本点之间差异的不足,并利用最小二乘法来取得最优的常数解;同时对所有的距离数据进行归一化处理,提高了算法准确度。最终实验表明了所提方法预测战场核心人物去往核心点的概率的有效性。

With the continuous development of the e-sports industry,except for the decisive factors such as experience,talent and skills,data analysis has an increasing influence on the winners and losers of MOBA games.For the problem that some MOBA games are unable to obtain accurate data directly through the interface,this paper proposed a method that gives pretreatment for position data according to the official heat maps and used PNN(Probabilistic Nearest Neighbor)with the idea of prototype clustering for tactical analysis.Finally,tactics is derived in the form of a probability:mobile probability for core characteristics of sides to core of the battle.In this algorithm,weighted distance is added to improve KNN’s shortcoming of using Euclidean distance to calculate the difference between sample points,and the least square method is used to obtain the optimal constant solution.At the same time,all distance data are normalized to improve the accuracy of the algorithm.The final experiment shows that this method is effective in predicting the probability of the core point of the battlefield.