Da
World of Books (was SecondSale), Montgomery, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Venditore AbeBooks dal 20 dicembre 2007
Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc. Codice articolo 00087521207
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective.What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming.We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations.
Titolo: Algorithms for Reinforcement Learning (...
Casa editrice: Morgan and Claypool Publishers
Data di pubblicazione: 2010
Legatura: Brossura
Condizione: Very Good
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Condizione: New. Codice articolo ABLIING23Mar3113020034765
Quantità: Più di 20 disponibili
Da: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9783031004230
Quantità: Più di 20 disponibili
Da: ALLBOOKS1, Direk, SA, Australia
Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address. Codice articolo SHAK302331
Quantità: 8 disponibili