Deep Reinforcement Learning

Frontiers of Artificial Intelligence

AvMohit Sewak

Häftad, Engelska, 2020

1 763 kr

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Beskrivning

This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in a number of applications.

Produktinformation

Utgivningsdatum:2020-08-15
Mått:155 x 235 x undefined mm
Format:Häftad
Språk:Engelska
Antal sidor:203
Förlag:Springer Verlag, Singapore
ISBN:9789811382871

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Mer om författaren

Mr. Sewak has been the Lead Data Scientist/Analytics Architect for a number of important international AI/DL/ML software and industry solutions and has also been involved in providing solutions and research for a series of cognitive features for IBM Watson Commerce. He has 14 years of experience working as a solutions architect using technologies like TensorFlow, Torch, Caffe, Theano, Keras, Open AI, SpaCy, Gensim, NLTK, Watson, SPSS, Spark, H2O, Kafka, ES, and others.

Innehållsförteckning

Introduction to Reinforcement Learning.- Mathematical and Algorithmic understanding of Reinforcement Learning.- Coding the Environment and MDP Solution.- Temporal Difference Learning, SARSA, and Q Learning.- Q Learning in Code.- Introduction to Deep Learning.- Implementation Resources.- Deep Q Network (DQN), Double DQN and Dueling DQN.- Double DQN in Code.- Policy-Based Reinforcement Learning Approaches.- Actor-Critic Models & the A3C.- A3C in Code.- Deterministic Policy Gradient and the DDPG.- DDPG in Code.