Introduction to Learning Classifier Systems

✍ Scribed by Ryan J. Urbanowicz, Will N. Browne

Publisher: Springer
Year: 2017
Tongue: English
Leaves: 132
Category: Library

⬇ Acquire This Volume

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Introduction to Learning Classifier Syst

📁 Introduction to Learning Classifier Systems

✍ Browne, Will N.; Urbanowicz, Ryan J 📂 Library 📅 2017 🏛 Springer Berlin Heidelberg 🌐 English

This accessible introduction shows the reader how to understand, implement, adapt, and apply Learning Classifier Systems (LCSs) to interesting and difficult problems. The text builds an understanding from basic ideas and concepts. The authors first explore learning through environment interaction, a

Systems That Learn: An Introduction to L

📁 Systems That Learn: An Introduction to Learning Theory

✍ Jain S., Osherson D., Royer J.S., Sharma A. 📂 Library 📅 1999 🏛 MIT 🌐 English

Formal learning theory is one of several mathematical approaches to the study of intelligent adaptation to the environment. The analysis developed in this book is based on a number theoretical approach to learning and uses the tools of recursive-fun

Anticipatory Learning Classifier Systems

📁 Anticipatory Learning Classifier Systems

✍ Martin V. Butz (auth.) 📂 Library 📅 2002 🏛 Springer US 🌐 English

Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an envir

Learning classifier systems: From founda

📁 Learning classifier systems: From foundations to applications

✍ Pier Luca Lanzi 📂 Library 📅 2000 🏛 Springer 🌐 English

Learning Classifier Systems: From Founda

📁 Learning Classifier Systems: From Foundations to Applications

✍ John H. Holland, Lashon B. Booker, Marco Colombetti, Marco Dorigo, David E. Gold 📂 Library 📅 2000 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This boo

Introduction to Classical Integrable Sys

📁 Introduction to Classical Integrable Systems

✍ Olivier Babelon, Denis Bernard, Michel Talon 📂 Library 📅 2007 🏛 Cambridge University Press 🌐 English

Introducing the reader to classical integrable systems and their applications, this book synthesizes the different approaches to the subject, providing a set of interconnected methods for solving problems in mathematical physics. The authors introduce and explain each method, and demonstrate how it