Autonomous learning derived from experimental modeling of physical laws
- Author
- GRABEC, Igor1
[1] Amanova, Technology Park 18, Ljubljana, Slovenia - Issue title
- Special Issue on Autonomous Learning
- Author (monograph)
- ROY, Asim (Editor)1 ; APOLLONI, Bruno (Editor)2 ; PERLOVSKY, Leonid (Editor)3 ; MINAI, Ali (Editor)4
[1] Arizona State University, United States
[2] University of Milan, Italy
[3] Harvard University and the Air Force Research Laboratory, United States
[4] University of Cincinnati, United States - Source
Neural networks. 2013, Vol 41, pp 51-58, 8 p ; ref : 1/4 p
- ISSN
- 0893-6080
- Scientific domain
- Cognition; Electronics; Computer science; Neurology
- Publisher
- Elsevier, Kidlington
- Publication country
- United Kingdom
- Document type
- Article
- Language
- English
- Author keyword
- Autonomous learning Data compression Gaussian mixture model Information cost function Prototype samples Traffic flow
- Keyword (fr)
- Approche probabiliste Autoapprentissage Autoorganisation Bruit aléatoire Classification automatique Compression donnée Coopération Ecoulement trafic Entropie Erreur estimation Estimation densité Excitabilité Fonction coût Fonction densité probabilité Gestion trafic Modélisation Mélange loi probabilité Neurone Processus Gauss Prototype Redondance Système acquisition donnée Modèle donnée
- Keyword (en)
- Probabilistic approach Self learning Self organization Random noise Automatic classification Data compression Cooperation Traffic flow Entropy Estimation error Density estimation Excitability Cost function Probability density function Traffic management Modeling Mixed distribution Neuron Gaussian process Prototype Redundancy Data acquisition system Data models
- Keyword (es)
- Enfoque probabilista Autodidactismo Autoorganización Ruido aleatorio Clasificación automática Compresión dato Cooperación Flujo tráfico Entropía Error estimación Estimación densidad Excitabilidad Función coste Función densidad probabilidad Gestión tráfico Modelización Mezcla ley probabilidad Neurona Proceso Gauss Prototipo Redundancia Sistema adquisición dato Modelo de datos
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02B Software / 001D02B07 Memory organisation. Data processing / 001D02B07B Data processing. List processing. Character string processing
- Discipline
- Computer science : theoretical automation and systems
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 27398487
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Access to the document
Install on your browser
DOI
10.1016/j.neunet.2012.07.002 
https://dx.doi.org/10.1016/j.neunet.2012.07.002
"O:13:\"PanistOpenUrl\":36:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000idc\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:28:\"10.1016\/j.neunet.2012.07.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:9:\"\u0000*\u0000jtitle\";s:15:\"Neural networks\";s:9:\"\u0000*\u0000stitle\";s:11:\"Neural netw\";s:7:\"\u0000*\u0000date\";s:4:\"2013\";s:9:\"\u0000*\u0000volume\";s:2:\"41\";s:8:\"\u0000*\u0000issue\";s:0:\"\";s:8:\"\u0000*\u0000spage\";s:2:\"51\";s:8:\"\u0000*\u0000epage\";s:2:\"58\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0893-6080\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:6:\"GRABEC\";s:10:\"\u0000*\u0000aufirst\";s:4:\"Igor\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:0:{}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:0:\"\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:36:\"Special Issue on Autonomous Learning\";s:8:\"\u0000*\u0000title\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:8:\"\u0000*\u0000place\";s:10:\"Kidlington\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"8\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Panist access
"O:12:\"IstexOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:28:\"10.1016\/j.neunet.2012.07.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:9:\"\u0000*\u0000jtitle\";s:15:\"Neural networks\";s:9:\"\u0000*\u0000stitle\";s:11:\"Neural netw\";s:7:\"\u0000*\u0000date\";s:4:\"2013\";s:9:\"\u0000*\u0000volume\";s:2:\"41\";s:8:\"\u0000*\u0000issue\";s:0:\"\";s:8:\"\u0000*\u0000spage\";s:2:\"51\";s:8:\"\u0000*\u0000epage\";s:2:\"58\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0893-6080\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:6:\"GRABEC\";s:10:\"\u0000*\u0000aufirst\";s:4:\"Igor\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:0:{}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:0:\"\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:36:\"Special Issue on Autonomous Learning\";s:8:\"\u0000*\u0000title\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:8:\"\u0000*\u0000place\";s:10:\"Kidlington\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"8\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Istex access
"O:16:\"UnpaywallOpenUrl\":35:{s:8:\"\u0000*\u0000email\";s:27:\"assistance-portail@inist.fr\";s:6:\"\u0000*\u0000fmt\";N;s:6:\"\u0000*\u0000doi\";s:28:\"10.1016\/j.neunet.2012.07.002\";s:6:\"\u0000*\u0000pii\";N;s:7:\"\u0000*\u0000pmid\";N;s:9:\"\u0000*\u0000atitle\";N;s:9:\"\u0000*\u0000jtitle\";N;s:9:\"\u0000*\u0000stitle\";N;s:7:\"\u0000*\u0000date\";N;s:9:\"\u0000*\u0000volume\";N;s:8:\"\u0000*\u0000issue\";N;s:8:\"\u0000*\u0000spage\";N;s:8:\"\u0000*\u0000epage\";N;s:8:\"\u0000*\u0000pages\";N;s:7:\"\u0000*\u0000issn\";N;s:8:\"\u0000*\u0000eissn\";N;s:9:\"\u0000*\u0000aulast\";N;s:10:\"\u0000*\u0000aufirst\";N;s:9:\"\u0000*\u0000auinit\";N;s:10:\"\u0000*\u0000auinitm\";N;s:5:\"\u0000*\u0000au\";N;s:9:\"\u0000*\u0000aucorp\";N;s:7:\"\u0000*\u0000isbn\";N;s:8:\"\u0000*\u0000coden\";N;s:8:\"\u0000*\u0000genre\";N;s:7:\"\u0000*\u0000part\";N;s:9:\"\u0000*\u0000btitle\";N;s:8:\"\u0000*\u0000title\";N;s:8:\"\u0000*\u0000place\";N;s:6:\"\u0000*\u0000pub\";N;s:10:\"\u0000*\u0000edition\";N;s:9:\"\u0000*\u0000tpages\";N;s:9:\"\u0000*\u0000series\";N;s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";N;}"
Unpaywall access
"O:16:\"EuropePMCOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:28:\"10.1016\/j.neunet.2012.07.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:9:\"\u0000*\u0000jtitle\";s:15:\"Neural networks\";s:9:\"\u0000*\u0000stitle\";s:11:\"Neural netw\";s:7:\"\u0000*\u0000date\";s:4:\"2013\";s:9:\"\u0000*\u0000volume\";s:2:\"41\";s:8:\"\u0000*\u0000issue\";s:0:\"\";s:8:\"\u0000*\u0000spage\";s:2:\"51\";s:8:\"\u0000*\u0000epage\";s:2:\"58\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0893-6080\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:6:\"GRABEC\";s:10:\"\u0000*\u0000aufirst\";s:4:\"Igor\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:0:{}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:0:\"\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:36:\"Special Issue on Autonomous Learning\";s:8:\"\u0000*\u0000title\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:8:\"\u0000*\u0000place\";s:10:\"Kidlington\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"8\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Europe PubMed Central access
"O:11:\"BaseOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:28:\"10.1016\/j.neunet.2012.07.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:9:\"\u0000*\u0000jtitle\";s:15:\"Neural networks\";s:9:\"\u0000*\u0000stitle\";s:11:\"Neural netw\";s:7:\"\u0000*\u0000date\";s:4:\"2013\";s:9:\"\u0000*\u0000volume\";s:2:\"41\";s:8:\"\u0000*\u0000issue\";s:0:\"\";s:8:\"\u0000*\u0000spage\";s:2:\"51\";s:8:\"\u0000*\u0000epage\";s:2:\"58\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0893-6080\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:6:\"GRABEC\";s:10:\"\u0000*\u0000aufirst\";s:4:\"Igor\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:0:{}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:0:\"\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:36:\"Special Issue on Autonomous Learning\";s:8:\"\u0000*\u0000title\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:8:\"\u0000*\u0000place\";s:10:\"Kidlington\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"8\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
Base Search access
"O:12:\"ArXivOpenUrl\":35:{s:10:\"\u0000*\u0000openUrl\";N;s:6:\"\u0000*\u0000fmt\";s:7:\"journal\";s:6:\"\u0000*\u0000doi\";s:28:\"10.1016\/j.neunet.2012.07.002\";s:6:\"\u0000*\u0000pii\";s:0:\"\";s:7:\"\u0000*\u0000pmid\";s:0:\"\";s:9:\"\u0000*\u0000atitle\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:9:\"\u0000*\u0000jtitle\";s:15:\"Neural networks\";s:9:\"\u0000*\u0000stitle\";s:11:\"Neural netw\";s:7:\"\u0000*\u0000date\";s:4:\"2013\";s:9:\"\u0000*\u0000volume\";s:2:\"41\";s:8:\"\u0000*\u0000issue\";s:0:\"\";s:8:\"\u0000*\u0000spage\";s:2:\"51\";s:8:\"\u0000*\u0000epage\";s:2:\"58\";s:8:\"\u0000*\u0000pages\";s:0:\"\";s:7:\"\u0000*\u0000issn\";s:9:\"0893-6080\";s:8:\"\u0000*\u0000eissn\";s:0:\"\";s:9:\"\u0000*\u0000aulast\";s:6:\"GRABEC\";s:10:\"\u0000*\u0000aufirst\";s:4:\"Igor\";s:9:\"\u0000*\u0000auinit\";s:0:\"\";s:10:\"\u0000*\u0000auinitm\";s:0:\"\";s:5:\"\u0000*\u0000au\";a:0:{}s:9:\"\u0000*\u0000aucorp\";s:0:\"\";s:7:\"\u0000*\u0000isbn\";s:0:\"\";s:8:\"\u0000*\u0000coden\";s:0:\"\";s:8:\"\u0000*\u0000genre\";s:7:\"article\";s:7:\"\u0000*\u0000part\";s:0:\"\";s:9:\"\u0000*\u0000btitle\";s:36:\"Special Issue on Autonomous Learning\";s:8:\"\u0000*\u0000title\";s:71:\"Autonomous learning derived from experimental modeling of physical laws\";s:8:\"\u0000*\u0000place\";s:10:\"Kidlington\";s:6:\"\u0000*\u0000pub\";s:8:\"Elsevier\";s:10:\"\u0000*\u0000edition\";s:0:\"\";s:9:\"\u0000*\u0000tpages\";s:1:\"8\";s:9:\"\u0000*\u0000series\";s:0:\"\";s:8:\"\u0000*\u0000proxy\";s:30:\"http:\/\/proxyout.inist.fr:8080\/\";s:12:\"\u0000*\u0000integrite\";b:1;}"
arXiv access
