{"product_id":"reinforcement-learning-from-scratch-understanding-current-approaches-with-examples-in-java-and-greenfoot-hardcover","title":"Reinforcement Learning from Scratch: Understanding Current Approaches - With Examples in Java and Greenfoot - Hardcover","description":"\u003cp\u003eby \u003cb\u003eUwe Lorenz\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eIn 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? \u003c\/p\u003e \u003cp\u003eWith 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. \u003c\/p\u003eThe 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.\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eIn 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? \u003c\/p\u003e\u003cp\u003eWith 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. \u003c\/p\u003e\u003cp\u003eThe 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. \u003c\/p\u003e \u003cp\u003e\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003eThis book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAfter 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, \u003cb\u003eUwe Lorenz\u003c\/b\u003e 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.\u003c\/p\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 184\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.5 x 9.21 x 6.14 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e October 28, 2022\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42719315951679,"sku":"9783031090295","price":174.94,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/476feea5fcfe4e7310c6fb5254b6a1c4.webp?v=1765085182","url":"https:\/\/dhlswag.com\/products\/reinforcement-learning-from-scratch-understanding-current-approaches-with-examples-in-java-and-greenfoot-hardcover","provider":"BBB","version":"1.0","type":"link"}