- Learn Unity ML-Agents:Fundamentals of Unity Machine Learning
- Micheal Lanham
- 248字
- 2021-08-13 15:58:23
Machine Learning
Games and simulations are no stranger to AI technologies and there are numerous assets available to the Unity developer in order to provide simulated machine intelligence. These technologies include content like Behavior Trees, Finite State Machine, navigation meshes, A*, and other heuristic ways game developers use to simulate intelligence. So, why Machine Learning and why now? After all, many of the base ML techniques, like neural nets, we will use later in this book have been used in games before.
The reason, is due in large part to the OpenAI initiative, an initiative that encourages research across academia and the industry to share ideas and research on AI and ML. This has resulted in an explosion of growth in new ideas, methods, and areas for research. This means for games and simulations that we no longer have to fake or simulate intelligence. Now, we can build agents that learn from their environment and even learn to beat their human builders.
- Effective Amazon Machine Learning
- SQL Server 2008數據庫應用技術(第二版)
- 企業大數據系統構建實戰:技術、架構、實施與應用
- Neural Network Programming with TensorFlow
- 深度剖析Hadoop HDFS
- 數亦有道:Python數據科學指南
- 企業級數據與AI項目成功之道
- 深入淺出Greenplum分布式數據庫:原理、架構和代碼分析
- SQL Server 2012數據庫管理教程
- 中文版Access 2007實例與操作
- Unity 2018 By Example(Second Edition)
- Access數據庫開發從入門到精通
- 領域驅動設計精粹
- 數據挖掘算法實踐與案例詳解
- 標簽類目體系:面向業務的數據資產設計方法論