Reinforcement learning state-of-the-art

Reinforcement learning state-of-the-art

Saved in:

Bibliographic Details
Other Authors:	Otterlo, Martijn van, Wiering, Marco
Format:	Book
Published:	Heidelberg Springer 2012
Series:	Adaptation, learning and optimization v 12
Subjects:	Reinforcement learning
Online Access:	Click Here to View Status and Holdings.
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Qualitative spatial abstraction in reinforcement learning
by: Frommberger, Lutz
Published: (2010)

Adaptive representations for reinforcement learning
by: Whiteson, Shimon
Published: (2010)

Revitalising construction project procurement through joint risk management and integrated teams
by: Rahman, Motiar
Published: (2010)

Introduction to Deep Learning
by: Charniak, Eugene
Published: (2018)

Preference learning
Published: (2010)

Machine learning principles and techniques
Published: (1989)

Computational learning and probabilistic reasoning
Published: (1996)

Elements of machine learning
by: Langley, Pat
Published: (1996)

Introduction to machine learning
by: Alpaydin, Ethem

Machine learning neural networks, genetic algorithms, and fuzzy systems
by: Adeli, Hojjat 1950-
Published: (1995)

Ensemble machine learning methods and applications
Published: (2012)

Recruitment learning
by: Diederich, Joachim
Published: (2010)

Emerging paradigms in machine learning
Published: (2013)

Machine learning an algorithmic perspective
by: Marsland, Stephen
Published: (2009)

Utility-based learning from data
by: Friedman, Craig
Published: (2011)

Computational learning theory and natural learning systems edited by Stephen Jose Hanson ... (et al.)
Published: (1994)

Computational learning theory an introduction
by: Anthony, Martin
Published: (1992)

Machine learning ECML 2002 : 13th European Conference on Machine Learning, Helsinki, Finland, August 19-23, 2002 : proceedings
Published: (2002)

Computational learning theory and natural learning systems edited by Jose Hanson, George A. Drastal and Ronald L. Rivest
Published: (1994)

Learning kernel classifiers theory and algorithms
by: Herbrich, Ralf
Published: (2002)

Algorithmic learning theory II
Published: (1992)

Machine learning paradigms and methods
Published: (1990)

Rule-based evolutionary online learning systems a principled approach to LCS analysis and design
by: Butz, Martin V. 1975-
Published: (2006)

Machine learning an artificial intelligence approach
Published: (1983)

Foundations of Machine Learning
by: Mohri, Mehryar, et al.
Published: (2018)

The design and analysis of efficient learning algorithms
by: Schapire, Robert E.
Published: (1992)

Multistrategy learning
Published: (1993)

Cost-sensitive machine learning
Published: (2012)

Computer systems that learn Classification and prediction methods from statistics, neural nets, machine learning, and expert systems
by: Weiss, Sholom M.
Published: (1991)

The nature of statitical learning theory
by: Vapnik, Vladimir Naumovich
Published: (1995)

Machine learning and data mining methods and applications
Published: (1998)

Knowledge acquisition and machine learning theory, methods, and applications
Published: (1993)

Learning with kernels support vector machines , regularization, optimization and beyond
by: Scholkopf, Bernhard
Published: (2002)

Truth from trash how learning makes sense
by: Thornton, Christopher James
Published: (2002)

Connectionist approaches to language learning
Published: (1991)

Machine Learning For Absolute Beginners A Plain English Introduction
by: Theobald, Oliver
Published: (2017)

An introduction to computational learning theory
by: Kearns, Michael J
Published: (1997)

Machines that learn based on the principles of emporical control
by: Brown, Robert Alan 1938-
Published: (1994)

Rule extraction from support vector machines
Published: (2008)

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow Concepts, Tools, and Techniques to Build Intelligent Systems
by: Geron, Aurelien
Published: (2019)