with open AI, tensorflow and keras using python Nandy, Abhishek creator Biswas, Manisha. text xxu New York Apress 2019 2018 1st ed. monographic eng xiii, 167p. ; 23 cm. Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You'll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov's Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before looking at Open AI Gym. You'll then learn about Swarm Intelligence with Python in terms of reinforcement learning. The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There's also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google's Deep Mind and see scenarios where reinforcement learning can be used. You will: Absorb the core concepts of the reinforcement learning process Use advanced topics of deep learning and AI Work with Open AI Gym, Open AI, and Python Harness reinforcement learning with TensorFlow and Keras using Python. Chapter 1: Reinforcement Learning basics -- Chapter 2: Theory and Algorithms -- Chapter 3: Open AI basics -- Chapter 4: Getting to know Open AI and Open AI Gym the developers way -- Chapter 5: Reinforcement learning using Tensor Flow environment and Keras -- Chapter 6 Google's DeepMind and the future of Reinforcement Learning. By Abhishek Nandy andManisha Biswas. Reinforcement learning basics OpenAI basics Applying python to reinforcement learning Python 006.3 NANA (DLC) 2017962867 9781484232859 2019765102 DLC 171207 20220426110146.0 21819376 eng