League of Legends (LoL) is the most widely played multiplayer online battle arena (MOBA) game in the world. An important aspect of LoL is competitive ranked play, which utilizes a skill-based matchmaking system to form fair teams. However, players' skill levels vary widely depending on which champion, or hero, that they choose to play as. In this paper, we propose a method for predicting game outcomes in ranked LoL games based on players' experience with their selected champion. Using a deep neural network, we found that game outcomes can be predicted with 75.1% accuracy after all players have selected champions, which occurs before gameplay begins. Our results have important implications for playing LoL and matchmaking. Firstly, individual champion skill plays a significant role in the outcome of a match, regardless of team composition. Secondly, even after the skill-based matchmaking, there is still a wide variance in team skill before gameplay begins. Finally, players should only play champions that they have mastered, if they want to win games.
Synthesizing multi-layer perceptron network with ant lion, biogeography-based dragonfly algorithm evolutionary strategy invasive weed and league champion optimization hybrid algorithms in predicting heating load in residential buildings
CYRUS Soccer Simulation 2D Team Description Paper 2022
Dalhousie University（达尔豪斯大学）；Amirkabir University of Technology（阿米尔卡比尔理工大学）；Qom University of Technology（库姆理工大学）；Shiraz University（设拉子大学）；Polish Academy of Sciences（波兰科学院）；Memorial University of Newfoundland（纽芬兰纪念大学）
Mastering Strategy Card Game (Legends of Code and Magic) via End-to-End Policy and Optimistic Smooth Fictitious Play
ByteDance（字节跳动）
深度强化学习结合Fictionary Play在许多基准测试游戏上显示出令人印象深刻的结果，然而，其中大多数都是单阶段的。相比之下，现实世界的决策问题可能由多个阶段组成，其中观察空间和行动空间在各个阶段之间可能完全不同。我们研究了一个两阶段的策略纸牌游戏Legends of Code and Magic，并提出了一个端到端的策略来解决多阶段游戏中出现的困难。我们还提出了一个乐观光滑虚拟博弈算法来寻找两人博弈的纳什均衡。我们的方法赢得了COG2022比赛的双重冠军。大量的研究验证并显示了我们方法的先进性。
Improving Dribbling, Passing, and Marking Actions in Soccer Simulation 2D Games Using Machine Learning
Institute for Big Data Analytics, Dalhousie University（达尔豪斯大学大数据分析研究所）；Qom University of Technology（库姆科技大学）；Shiraz University（设拉子大学）；Amirkabir University of Technology（阿米尔卡比尔理工大学）；Institute for Computer Science, Polish Academy of Sciences（波兰科学院计算机科学研究所）；Memorial University of Newfoundland（纽芬兰纪念大学）
本文介绍了 RoboCup 2021 2D 足球仿真冠军 CYRUS 的三大核心功能：多动作盘带、传球预测和盯人决策，分别提升了盘带成功率、团队协作和防守策略。
