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.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Verstärkungslernen
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Über diesen Kurs
Probabilities & Expectations, basic linear algebra, basic calculus, Python 3.0 (at least 1 year), implementing algorithms from pseudocode
Kompetenzen, die Sie erwerben
- Artificial Intelligence (AI)
- Machine Learning
- Reinforcement Learning
- Function Approximation
- Intelligent Systems
Probabilities & Expectations, basic linear algebra, basic calculus, Python 3.0 (at least 1 year), implementing algorithms from pseudocode
Lehrplan - Was Sie in diesem Kurs lernen werden
Welcome to the Course!
Monte Carlo Methods for Prediction & Control
Temporal Difference Learning Methods for Prediction
Temporal Difference Learning Methods for Control
Planning, Learning & Acting
Bewertungen
- 5 stars81,99 %
- 4 stars13,63 %
- 3 stars2,79 %
- 2 stars0,61 %
- 1 star0,96 %
Top-Bewertungen von SAMPLE-BASED LEARNING METHODS
The lectures and quiz tests are perfect. Jupyter. Programming exercises can be a little confusing sometimes but are also great. A great course, overall.
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
definitely interesting subjects, but I do not like the teaching method. Very mechanic and dull, with not enough connection to the real world
Great course! The notebooks are a perfect level of difficulty for someone learning RL for the first time. Thanks Martha and Adam for all your work on this!! Great content!!
Über den Spezialisierung Verstärkungslernen

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