Reinforcement Learning From Scratch : Understanding Current Approaches - with Examples in Java and Greenfoot

Uwe Lorenz

ISBN 10: 3031090322 / ISBN 13: 9783031090325

Editore: Springer International Publishing, 2023

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Druck auf Anfrage Neuware - Printed after ordering - In ancient games such as chess or go, the most brilliant players can improve by studying the strategies produced by a machine. Robotic systems practice their own movements. In arcade games, agents capable of learning reach superhuman levels within a few hours. How do these spectacular reinforcement learning algorithms work With easy-to-understand explanations and clear examples in Java and Greenfoot, you can acquire the principles of reinforcement learning and apply them in your own intelligent agents. Greenfoot (M.Kölling, King's College London) and the hamster model (D. Bohles, University of Oldenburg) are simple but also powerful didactic tools that were developed to convey basic programming concepts.The result isan accessible introduction into machine learning that concentrates on reinforcement learning. Taking the reader through the steps of developing intelligent agents, from the very basics to advanced aspects, touching on a variety of machine learning algorithms along the way, one is allowedto play along, experiment, and add their own ideas and experiments.

Codice articolo 9783031090325

Dati bibliografici

• Titolo: Reinforcement Learning From Scratch : Understanding Current Approaches - with Examples in Java and Greenfoot
• Editore: Springer International Publishing
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 3031090322
• ISBN 13: 9783031090325
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 12 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 12 millimetri di profondità
• Peso: 312 grammi

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Riassunto

In ancient games such as chess or go, the most brilliant players can improve by studying the strategies produced by a machine. Robotic systems practice their own movements. In arcade games, agents capable of learning reach superhuman levels within a few hours. How do these spectacular reinforcement learning algorithms work? 

With easy-to-understand explanations and clear examples in Java and Greenfoot, you can acquire the principles of reinforcement learning and apply them in your own intelligent agents. Greenfoot (M.Kölling, King's College London) and the hamster model (D. Bohles, University of Oldenburg) are simple but also powerful didactic tools that were developed to convey basic programming concepts. 

The result is an accessible introduction into machine learning that  concentrates on reinforcement learning. Taking the reader through the steps of developing intelligent agents, from the very basics to advanced aspects, touching on a variety of machine learning algorithms along the way, one is allowed to play along, experiment, and add their own ideas and experiments.  

Informazioni sull?autore

After studying computer science and philosophy with a focus on artificial intelligence and machine learning at the Humboldt University Berlin and for a few years as a project engineer, Uwe Lorenz currently works as a high school teacher for computer science and mathematics and at the Free University of Berlin in the Computing Education Research Group, - since his first contact with computers at the end of the 1980s he couldn't let go of the topic of artificial intelligence.