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Bewertung und Feedback des Lernenden für Sample-based Learning Methods von University of Alberta

4.8
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1,100 Bewertungen
217 Bewertungen

Über den Kurs

In this course, you will learn about several algorithms that can learn near optimal policies based on trial and error interaction with the environment---learning from the agent’s own experience. Learning from actual experience is striking because it requires no prior knowledge of the environment’s dynamics, yet can still attain optimal behavior. We will cover intuitively simple but powerful Monte Carlo methods, and temporal difference learning methods including Q-learning. We will wrap up this course investigating how we can get the best of both worlds: algorithms that can combine model-based planning (similar to dynamic programming) and temporal difference updates to radically accelerate learning. By the end of this course you will be able to: - Understand Temporal-Difference learning and Monte Carlo as two strategies for estimating value functions from sampled experience - Understand the importance of exploration, when using sampled experience rather than dynamic programming sweeps within a model - Understand the connections between Monte Carlo and Dynamic Programming and TD. - Implement and apply the TD algorithm, for estimating value functions - Implement and apply Expected Sarsa and Q-learning (two TD methods for control) - Understand the difference between on-policy and off-policy control - Understand planning with simulated experience (as opposed to classic planning strategies) - Implement a model-based approach to RL, called Dyna, which uses simulated experience - Conduct an empirical study to see the improvements in sample efficiency when using Dyna...

Top-Bewertungen

DP

14. Feb. 2021

Excellent course that naturally extends the first specialization course. The application examples in programming are very good and I loved how RL gets closer and closer to how a living being thinks.

AA

11. Aug. 2020

Great course, giving it 5 stars though it deserves both because the assignments have some serious issues that shouldn't actually be a matter. All the other parts are amazing though. Good job

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101 - 125 von 216 Bewertungen für Sample-based Learning Methods

von Varun K R K

15. Mai 2021

The best course available on entire world for reinforcement learning

von Dan N

24. Okt. 2021

I liked that this course had programming assignments for each week.

von Animesh

28. Mai 2020

this course is very well designed and executed. wow! i loved it :D

von Li W

30. März 2020

Very good introductions and practices to the classic RL algorithms

von DEEP P

8. Juli 2020

Great learning Experience and really helpful lecturers and staff.

von Rudi C

21. Juli 2020

Wonderful course, highly instructive, and follows the textbook!

von Rajesh

2. Juli 2020

Please make assignments more explanatory and allow flexiblity

von Farzad E b

28. Juli 2022

It was great!! One of the best courses I've ever enrolled in

von alper d

17. Jan. 2021

Good course material and simplified explanations. Thank you.

von Da

3. Nov. 2019

Really a wonderful course! Very professional and high level.

von Teresa Y B

10. Apr. 2020

Very well structured course, Thanks for so nice preparing!!

von Shi Y

10. Nov. 2019

最喜欢的Coursera课程之一,难度适中的RL课程,非常推荐,学习到了很多自学很难理解全面的知识。感谢老师和助教们!

von Alex E

19. Nov. 2019

A fun an interesting course. Keep up the great work!

von Jicheng F

11. Juli 2020

Martha and Adam are great instructors, great job!

von garcia b

31. Dez. 2019

very copacetic. excellent complement to the book

von Ignacio O

13. Okt. 2019

Great, informative and very interesting course.

von Ashish S

16. Sep. 2019

A good course with proper Mathematical insights

von Guruprasad

13. Juli 2021

very intutive and the instructors are succinct

von Cheuk L Y

3. Juli 2020

Very good overall! It takes time to digest.

von LIWANGZHI

15. Jan. 2020

A nice course with well-designed homework:)

von Jingxin X

26. Mai 2020

Very helpful follow up tot he first one.

von Ryan Y

17. Jan. 2021

Better than reading the textbook alone.

von Sriram R

20. Okt. 2019

Well done mix of theory and practice!

von Luiz C

13. Sep. 2019

Great Course. Every aspect top notch

von David I

19. Apr. 2020

very good course with good examples