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You're reading from  Mastering Reinforcement Learning with Python

Product typeBook
Published inDec 2020
Reading LevelBeginner
PublisherPackt
ISBN-139781838644147
Edition1st Edition
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Author (1)
Enes Bilgin
Enes Bilgin
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Enes Bilgin

Enes Bilgin works as a senior AI engineer and a tech lead in Microsoft's Autonomous Systems division. He is a machine learning and operations research practitioner and researcher with experience in building production systems and models for top tech companies using Python, TensorFlow, and Ray/RLlib. He holds an M.S. and a Ph.D. in systems engineering from Boston University and a B.S. in industrial engineering from Bilkent University. In the past, he has worked as a research scientist at Amazon and as an operations research scientist at AMD. He also held adjunct faculty positions at the McCombs School of Business at the University of Texas at Austin and at the Ingram School of Engineering at Texas State University.
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Summary

In this chapter, we covered three important approaches to solving MDPs: Dynamic programming, Monte Carlo methods, and temporal-difference learning. We have seen that while DP provides exact solutions to MDPs, it requires knowing the precise dynamics of an environment. Monte Carlo and TD learning methods, on the other hand, explore in the environment and learn from experience. TD learning, in particular, can learn from even a single step transitions in the environment. Within the chapter, we also presented on-policy methods, which estimate the value functions for a behavior policy, while off-policy methods for a target policy. Finally, we discussed the importance of the simulator in RL experiments and what to pay attention to when working with one.

Next, we take our journey to a next level and dive into deep reinforcement learning, which will enable us to solve some complex real-world problems. Particularly, in the next chapter, we cover deep Q-learning in detail.

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Mastering Reinforcement Learning with Python
Published in: Dec 2020Publisher: PacktISBN-13: 9781838644147

Author (1)

author image
Enes Bilgin

Enes Bilgin works as a senior AI engineer and a tech lead in Microsoft's Autonomous Systems division. He is a machine learning and operations research practitioner and researcher with experience in building production systems and models for top tech companies using Python, TensorFlow, and Ray/RLlib. He holds an M.S. and a Ph.D. in systems engineering from Boston University and a B.S. in industrial engineering from Bilkent University. In the past, he has worked as a research scientist at Amazon and as an operations research scientist at AMD. He also held adjunct faculty positions at the McCombs School of Business at the University of Texas at Austin and at the Ingram School of Engineering at Texas State University.
Read more about Enes Bilgin