ICALA: Incremental clustering and associative learning architecture

Matthias U. Keysermann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

I propose a learning and memory architecture which can incrementally learn and associate an increasing number of patterns. The approach consists of the integration of two methods - a topology learning algorithm to perform incremental clustering, and an associative memory model to learn relationships based on the co-occurrence of input patterns. The approach supports online learning, is tolerant to noise, and generally applicable to any kind of real-valued vector data. I tested the proposed architecture on an incremental associative learning task with visual patterns. Evaluations were performed both in a simulated setup and with a real robot. Results showed that the architecture could learn nearly all presented patterns but in some cases the recall rate decreased as these patterns were retrieved. I suggest ways to overcome this effect and also discuss future work aimed at achieving a better performance.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Pages70-79
Number of pages10
Volume8779 LNAI
ISBN (Print)9783319112978
DOIs
Publication statusPublished - 2014
Event3rd International Conference on Adaptive and Intelligent Systems - Bournemouth, United Kingdom
Duration: 8 Sep 201410 Sep 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8779 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference3rd International Conference on Adaptive and Intelligent Systems
Abbreviated titleICAIS 2014
CountryUnited Kingdom
CityBournemouth
Period8/09/1410/09/14

Keywords

  • Associative Learning
  • Clustering
  • Incremental Learning

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  • Cite this

    Keysermann, M. U. (2014). ICALA: Incremental clustering and associative learning architecture. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8779 LNAI, pp. 70-79). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8779 LNAI). Springer. https://doi.org/10.1007/978-3-319-11298-5_8