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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
Languages
Python
Tools
PyTorch
Concepts
Reinforcement Learning
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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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Why we need function approximations

While solving (contextual) multi-armed bandit problems, our goal is to learn action values for each arm (action) from our observations, which we have denoted by . In the online advertising example, it represented our estimate for the probability of a user clicking the ad if we displayed . Now, assume that we have two pieces of information about the user seeing the ad, namely:

  • Device type (e.g. mobile vs. desktop), and
  • Location (e.g. domestic / U.S. vs. international / non-U.S.)

It is quite likely that ad performances will differ with device type and location, which make up the context in this example. A CB model will therefore leverage this information, estimate the action values for each context, and choose the actions accordingly.

This would look like filling a table for each ad similar to the below:

Table 1 – Sample action values for ad D

This means solving four MAB problems, one for...

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

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