Book Image

Keras Reinforcement Learning Projects

By : Giuseppe Ciaburro
Book Image

Keras Reinforcement Learning Projects

By: Giuseppe Ciaburro

Overview of this book

Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library. The book begins with getting you up and running with the concepts of reinforcement learning using Keras. You’ll learn how to simulate a random walk using Markov chains and select the best portfolio using dynamic programming (DP) and Python. You’ll also explore projects such as forecasting stock prices using Monte Carlo methods, delivering vehicle routing application using Temporal Distance (TD) learning algorithms, and balancing a Rotating Mechanical System using Markov decision processes. Once you’ve understood the basics, you’ll move on to Modeling of a Segway, running a robot control system using deep reinforcement learning, and building a handwritten digit recognition model in Python using an image dataset. Finally, you’ll excel in playing the board game Go with the help of Q-Learning and reinforcement learning algorithms. By the end of this book, you’ll not only have developed hands-on training on concepts, algorithms, and techniques of reinforcement learning but also be all set to explore the world of AI.
Table of Contents (13 chapters)

Game theory

Game theory is the mathematical science that studies and analyzes the individual decisions of a subject in situations of conflict or strategic interaction with other rival subjects aimed at the maximum profit of each subject. In such situations, the decisions of one can influence the results achieved by the other(s), and vice versa, according to a feedback mechanism, by seeking competitive and/or cooperative solutions through models.

The theory of games has its distant origins in 1654 from a correspondence between Blaise Pascal and Pierre de Fermat, on the calculation of probabilities for gambling.

The expression game theory was first used by Émile Borel in the 1920s. Borel took care of the théorie des jeux, of zero-sum games with two players and tried to find a solution known as John von Neumann's concept of solving a zero-sum game.

The birth of modern...