Reinforcement Learning From Scratch - Uwe Lorenz

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Résumé :
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.K?lling, 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. ...

Biographie:
Uwe Lorenz war nach seinem Studium der Informatik und Philosophie mit Schwerpunkt K?nstliche Intelligenz und Maschinelles Lernen an der Humboldt-Universit?t in Berlin und einigen Jahren als Projektingenieur f?r 10 Jahr als Gymnasiallehrer f?r Informatik und Mathematik t?tig. Seit seinem Erstkontakt mit Computern Ende der 80er Jahre hat ihn das Thema K?nstliche Intelligenz nicht mehr losgelassen. Derzeit arbeitet er als wissenschaftlicher Mitarbeiter in der Arbeitsgruppe Didaktik der Informatik an der Freien Universit?t Berlin in einem Projekt zur Thematik Verantwortungsvolle K?nstliche Intelligenz in der Lehramtsausbildung....

Sommaire:
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.K?lling, 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. ...