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Opiniones y comentarios de aprendices correspondientes a Sample-based Learning Methods por parte de Universidad de Alberta

1,100 calificaciones

Acerca del Curso

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...

Principales reseñas


14 de feb. de 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.


11 de ago. de 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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126 - 150 de 216 revisiones para Sample-based Learning Methods

por Alejandro D

19 de sep. de 2019

Excellent content and delivery.

por Bekay K

4 de jul. de 2020

Great resource to learning RL


1 de jun. de 2020

Great Course by great faculty!

por Daniel W

18 de jul. de 2020

Hard but a really good course

por Pachi C

8 de dic. de 2019

Great and fantastic course!!!

por Sergey M

3 de oct. de 2021

Very well organized course!

por rashid K

12 de nov. de 2019

Best RL course ever done

por MD M R S

4 de mar. de 2021


por Venkatkumar R

3 de feb. de 2022

E​xcited to learn!

por Eleni F

15 de mar. de 2020

i really enjoy it!

por Mohamed A

19 de jul. de 2021

v​ery good course

por Guoxiang Z

7 de mar. de 2021

Very nice course!


7 de ago. de 2020

Brilliant Course!

por Antoni S D S

1 de jul. de 2021

Curso muito bom!

por Julio E F

29 de jun. de 2020

Amazing course!

por Santiago M C

20 de may. de 2020

excelent course

por Trần Q M

17 de feb. de 2020

wondrous course

por Max L

29 de sep. de 2020

great lecture


5 de sep. de 2020

Great course

por Antonio P

13 de dic. de 2019

Great Course

por John H

10 de nov. de 2019

It was good.

por Marconi S G

20 de ene. de 2022

Ótimo Curso

por Charles X

19 de jun. de 2021

Good course

por Oren

12 de abr. de 2020

Fun course!

por Jialong F

25 de feb. de 2021

learn much