课程信息
13,006 次近期查看

第 2 门课程(共 4 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

Probabilities & Expectations, basic linear algebra, basic calculus, Python 3.0 (at least 1 year), implementing algorithms from pseudocode

完成时间大约为21 小时

建议:4-6 hours/week...

英语(English)

字幕:英语(English)

您将获得的技能

Artificial Intelligence (AI)Machine LearningReinforcement LearningFunction ApproximationIntelligent Systems

第 2 门课程(共 4 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

Probabilities & Expectations, basic linear algebra, basic calculus, Python 3.0 (at least 1 year), implementing algorithms from pseudocode

完成时间大约为21 小时

建议:4-6 hours/week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 1 小时

Welcome to the Course!

2 个视频 (总计 10 分钟), 2 个阅读材料
2 个视频
Instructor Introductions8分钟
2 个阅读材料
Reinforcement Learning Textbook10分钟
Read Me: Pre-requisites and Learning Objectives10分钟
2
完成时间为 2 小时

Monte Carlo Methods for Prediction & Control

10 个视频 (总计 46 分钟), 2 个阅读材料, 1 个测验
10 个视频
Using Monte Carlo for Prediction6分钟
Using Monte Carlo for Action Values2分钟
Using Monte Carlo methods for generalized policy iteration2分钟
Solving the Blackjack Example3分钟
Epsilon-soft policies5分钟
Why does off-policy learning matter?4分钟
Importance Sampling4分钟
Off-Policy Monte Carlo Prediction5分钟
Week 1 Summary3分钟
2 个阅读材料
Weekly Reading10分钟
Chapter Summary10分钟
1 个练习
Graded Quiz
3
完成时间为 5 小时

Temporal Difference Learning Methods for Prediction

4 个视频 (总计 18 分钟), 1 个阅读材料, 2 个测验
4 个视频
The advantages of temporal difference learning5分钟
Comparing TD and Monte Carlo5分钟
Week 2 Summary2分钟
1 个阅读材料
Weekly Reading10分钟
1 个练习
Practice Quiz30分钟
4
完成时间为 7 小时

Temporal Difference Learning Methods for Control

9 个视频 (总计 30 分钟), 2 个阅读材料, 2 个测验
9 个视频
Sarsa in the Windy Grid World3分钟
What is Q-learning?3分钟
Q-learning in the Windy Grid World3分钟
How is Q-learning off-policy?4分钟
Expected Sarsa3分钟
Expected Sarsa in the Cliff World3分钟
Generality of Expected Sarsa1分钟
Week 3 Summary2分钟
2 个阅读材料
Weekly Reading10分钟
Chapter summary10分钟
1 个练习
Practice Quiz18分钟

讲师

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Martha White

Assistant Professor
Computing Science
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Adam White

Assistant Professor
Computing Science

关于 阿尔伯塔大学

UAlberta is considered among the world’s leading public research- and teaching-intensive universities. As one of Canada’s top universities, we’re known for excellence across the humanities, sciences, creative arts, business, engineering and health sciences....

关于 Alberta Machine Intelligence Institute

The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based research institute that pushes the bounds of academic knowledge and guides business understanding of artificial intelligence and machine learning....

关于 强化学习 专项课程

The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI). Harnessing the full potential of artificial intelligence requires adaptive learning systems. Learn how Reinforcement Learning (RL) solutions help solve real-world problems through trial-and-error interaction by implementing a complete RL solution from beginning to end. By the end of this Specialization, learners will understand the foundations of much of modern probabilistic artificial intelligence (AI) and be prepared to take more advanced courses or to apply AI tools and ideas to real-world problems. This content will focus on “small-scale” problems in order to understand the foundations of Reinforcement Learning, as taught by world-renowned experts at the University of Alberta, Faculty of Science. The tools learned in this Specialization can be applied to game development (AI), customer interaction (how a website interacts with customers), smart assistants, recommender systems, supply chain, industrial control, finance, oil & gas pipelines, industrial control systems, and more....
强化学习

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