Track My Order
Help Centre
1300 187 187
Likes
My Wish ListsLogin / Join
Booktopia
Australia's local bookstore

0 Item

Learning Classifier Systems : 5th International Workshop, IWLCS 2002, Granada, Spain, September 7-8, 2002, Revised Papers - Pier Luca Lanzi

eTEXT

Learning Classifier Systems

5th International Workshop, IWLCS 2002, Granada, Spain, September 7-8, 2002, Revised Papers

By: Pier Luca Lanzi, ?Wolfgang Stolzmann, ?Stewart W. Wilson

eText | 24 November 2003 | Edition Number 1

At a Glance

eText

$84.99

or 4 interest-free payments of $21.25 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Read online on
Desktop
Tablet
Mobile

Not downloadable to your eReader or an app

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.
The 5th International Workshop on Learning Classi?er Systems (IWLCS2002) was held September 7-8, 2002, in Granada, Spain, during the 7th International Conference on Parallel Problem Solving from Nature (PPSN VII). We have included in this volume revised and extended versions of the papers presented at the workshop. In the ?rst paper, Browne introduces a new model of learning classi?er system, iLCS, and tests it on the Wisconsin Breast Cancer classi?cation problem. Dixon et al. present an algorithm for reducing the solutions evolved by the classi?er system XCS, so as to produce a small set of readily understandable rules. Enee and Barbaroux take a close look at Pittsburgh-style classi?er systems, focusing on the multi-agent problem known as El-farol. Holmes and Bilker investigate the effect that various types of missing data have on the classi?cation performance of learning classi?er systems. The two papers by Kovacs deal with an important theoretical issue in learning classi?er systems: the use of accuracy-based ?tness as opposed to the more traditional strength-based ?tness. In the ?rst paper, Kovacs introduces a strength-based version of XCS, called SB-XCS. The original XCS and the new SB-XCS are compared in the second paper, where - vacs discusses the different classes of solutions that XCS and SB-XCS tend to evolve.
Read online on
Desktop
Tablet
Mobile

You Can Find This eBook In

Non-FictionComputing & I.T.Computer ScienceArtificial IntelligenceMathematicsMathematical FoundationMathematical LogicDatabases

More in Artificial Intelligence

AI-Powered Search - Trey Grainger

eBOOK

AI-Powered Search

eBook

$52.99

HBR Guide to Generative AI for Managers : HBR Guide - Elisa Farri

eBOOK

HBR Guide to Generative AI for Managers

HBR Guide

eBook

RRP $38.45

$30.99

19%
OFF
AI : The End of Human Race - Alex Wood

eBOOK

AI

The End of Human Race

eBook

$16.99

This product is categorised by