About: Learning classifier system

Facets (new session)
Description
Metadata
Settings
- Rule:
- Inverse Functional Properties:
- "Same As":

About: Learning classifier system Goto Sponge NotDistinct Permalink

An Entity of Type : yago:WikicatEvolutionaryAlgorithms, within Data Space : dbpedia.demo.openlinksw.com associated with source document(s)
QRcode icon

http://dbpedia.demo.openlinksw.com/describe/?url=http%3A%2F%2Fdbpedia.org%2Fresource%2FLearning_classifier_system

Learning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a genetic algorithm) with a learning component (performing either supervised learning, reinforcement learning, or unsupervised learning). Learning classifier systems seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions (e.g. behavior modeling, classification, data mining, regression, function approximation, or game strategy). This approach allows complex solution spaces to be broken up into smaller, simpler parts.

Attributes	Values
rdf:type	software yago:Abstraction100002137 yago:Act100030358 yago:Activity100407535 yago:Algorithm105847438 yago:Event100029378 yago:Procedure101023820 yago:PsychologicalFeature100023100 yago:YagoPermanentlyLocatedEntity yago:Rule105846932 yago:WikicatEvolutionaryAlgorithms
rdfs:label	Learning Classifier System (de) Système de classeurs (fr) Learning classifier system (en)
rdfs:comment	Un système de classeurs (Learning Classifier System ou LCS en anglais) est un système d'apprentissage automatique utilisant l'apprentissage par renforcement et les algorithmes génétiques. Ils ont été introduits par Holland en 1977 et développé par Goldberg en 1989 (fr) Ein Learning Classifier System (LCS, deutsch Lernende Klassifikatorsysteme) ist ein Verfahren des maschinellen Lernens, bei dem evolutionäre Algorithmen mit klassischen Lernalgorithmen kombiniert werden, um adaptive Systeme zu erzeugen. (de) Learning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a genetic algorithm) with a learning component (performing either supervised learning, reinforcement learning, or unsupervised learning). Learning classifier systems seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions (e.g. behavior modeling, classification, data mining, regression, function approximation, or game strategy). This approach allows complex solution spaces to be broken up into smaller, simpler parts. (en)
foaf:depiction
dcterms:subject	Evolutionary algorithms
Wikipage page ID	854461 (xsd:integer)
Wikipage revision ID	1105272150 (xsd:integer)
Link from a Wikipage to another Wikipage	Q-learning Epidemiology Epistasis Mutation (genetic algorithm) Boolean data type Decision tree Dependent and independent variables Estimation of distribution algorithm Genetic programming Online machine learning Class (set theory) Genetic algorithm Crossover (genetic algorithm) Machine learning Stochastic Complex adaptive system Feasible region Feature selection Function approximation Population-based incremental learning Strategy (game theory) Data mining Latent learning Graphical user interface Kenneth A De Jong Production system (computer science) Random forest Regression analysis Reinforcement learning Artificial intelligence Artificial neural network John Henry Holland Binary number Bioinformatics Holland's schema theorem Homogeneity and heterogeneity Tournament selection Artificial immune system Evolutionary algorithms Association rule learning Phenotype Multiplexer Statistical classification Expert system Unsupervised learning Offline learning Rule-based machine learning Evolutionary algorithm Piecewise Knowledge discovery Scalability Overfitting Supervised learning Training data set Behavior modeling Roulette wheel selection
Link from a Wikipage to an external page	http://gbml.org/ http://prediction-dynamics.com/ https://www.youtube.com/watch%3Fv=CRge_cZ2cJc http://www.cems.uwe.ac.uk/lcsg/
sameAs	Learning classifier system Learning classifier system Learning classifier system Learning classifier system Learning classifier system Learning classifier system Learning classifier system
dbp:wikiPageUsesTemplate	dbt:Reflist dbt:Short_description
thumbnail	wiki-commons:Special:FilePath/Function_approximation_with_LCS_rules.jpg?width=300
has abstract	Ein Learning Classifier System (LCS, deutsch Lernende Klassifikatorsysteme) ist ein Verfahren des maschinellen Lernens, bei dem evolutionäre Algorithmen mit klassischen Lernalgorithmen kombiniert werden, um adaptive Systeme zu erzeugen. Diese Systeme basieren auf Regeln, die traditionell die Form der bedingten Anweisung (Wenn-Dann) aufweisen. Diese Regeln sollen das bestmögliche Verhalten aufgrund einer bestimmten Eingabe (englisch input) ausführen. Sie werden dazu mit einem evolutionären Algorithmus angepasst. Prinzipiell sind vor allem die Pittsburgh-Type-LCS, in denen separate Populationen von Regeln angepasst werden, von den Michigan-Style-LCS zu unterscheiden. In letzteren werden einzelne Regeln evolviert und keine kompletten Regelsätze. (de) Learning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a genetic algorithm) with a learning component (performing either supervised learning, reinforcement learning, or unsupervised learning). Learning classifier systems seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions (e.g. behavior modeling, classification, data mining, regression, function approximation, or game strategy). This approach allows complex solution spaces to be broken up into smaller, simpler parts. The founding concepts behind learning classifier systems came from attempts to model complex adaptive systems, using rule-based agents to form an artificial cognitive system (i.e. artificial intelligence). (en) Un système de classeurs (Learning Classifier System ou LCS en anglais) est un système d'apprentissage automatique utilisant l'apprentissage par renforcement et les algorithmes génétiques. Ils ont été introduits par Holland en 1977 et développé par Goldberg en 1989 (fr)
gold:hypernym	Machine
prov:wasDerivedFrom	wikipedia-en:Learning_classifier_system?oldid=1105272150&ns=0
page length (characters) of wiki page	51518 (xsd:nonNegativeInteger)

Faceted Search & Find service v1.17_git139 as of Feb 29 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 08.03.3330 as of Mar 19 2024, on Linux (x86_64-generic-linux-glibc212), Single-Server Edition (378 GB total memory, 67 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software