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Reinforcement Learning with TensorFlow
book

Reinforcement Learning with TensorFlow

by Sayon Dutta
April 2018
Intermediate to advanced content levelIntermediate to advanced
334 pages
10h 18m
English
Packt Publishing
Content preview from Reinforcement Learning with TensorFlow

Programming an agent using an OpenAI Gym environment

The environment considered for this section is the Frozen Lake v0. The actual documentation of the concerned environment can be found at https://gym.openai.com/envs/FrozenLake-v0/.

This environment consists of 4 x 4 grids representing a lake. Thus, we have 16 grid blocks, where each block can be a start block(S), frozen block(F), goal block(G), or a hole block(H). Thus, the objective of the agent is to learn to navigate from start to goal without falling in the hole:

import Gymenv = Gym.make('FrozenLake-v0')    #loads the environment FrozenLake-v0env.render()                       # will output the environment and position of the agent-------------------SFFF
FHFH
FFFH
HFFG

At any given state, an agent has four ...

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Publisher Resources

ISBN: 9781788835725Supplemental Content