Lifelong learning approach to intelligent agents modeling

Witold Jacak, Stephan Dreiseitl

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

In this paper, we presented an application of neural network-based models in the intelligent agent domain. The use of neural networks has the advantage that the model can adapt itself to changing environment conditions by simple retraining steps. This is illustrated by two functions needed for the lifelong learning-based modeling of an intelligent robotic agent: The function for generalizing sensor observations to conceptual states, and the function for modeling the effects of robot actions on the conceptual state space. An example shows that the algorithms can be applied in real-world environments.

Original languageEnglish
Title of host publicationComputer Aided Systems Theory - EUROCAST 1997 - A Selection of Papers from the 6th International Workshop on Computer Aided Systems Theory, Proceedings
EditorsFranz Pichler, Roberto Moreno-Diaz
PublisherSpringer Verlag
Pages367-379
Number of pages13
ISBN (Print)3540638113, 9783540638117
DOIs
Publication statusPublished - 1997
Event6th International Workshop on Computer Aided Systems Theory, EUROCAST 1997 - Las Palmas de Gran Canaria, Spain
Duration: 24 Feb 199728 Feb 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1333
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Workshop on Computer Aided Systems Theory, EUROCAST 1997
CountrySpain
CityLas Palmas de Gran Canaria
Period24.02.199728.02.1997

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