Draft-Analysis of the Ancients: Predicting Draft Picks in DotA 2 using Machine Learning

Author:

Summerville Adam,Cook Michael,Steenhuisen Ben

Abstract

Analysing strategic decision-making in eSports is an increasingly important problem -- for players, for teams, for commentators, for viewers and for broadcasters. Such analysis is extremely difficult, however, because of the comparatively small quantities of data, the ever-shifting state of competitive play, and the huge complexity of the game. In this paper we describe a system for predicting drafting decisions in DOTA 2, and evaluate both how the system performs compared to human experts, as well as the new kinds of analysis made possible by automation.

Publisher

Association for the Advancement of Artificial Intelligence (AAAI)

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. BPCoach: Exploring Hero Drafting in Professional MOBA Tournaments via Visual Analytics;Proceedings of the ACM on Human-Computer Interaction;2024-04-17

2. An Integrated Framework for Team Formation and Winner Prediction in the FIRST Robotics Competition: Model, Algorithm, and Analysis;2023 IEEE International Conference on High Performance Computing & Communications, Data Science & Systems, Smart City & Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys);2023-12-17

3. Mining Player Behavior Patterns from Domain-Based Spatial Abstraction in Games;2023 IEEE Conference on Games (CoG);2023-08-21

4. A Pre-game Item Recommendation Method Based on Self-Supervised Learning;2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI);2023-08-18

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