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An Immune Learning Classifier Network for Autonomous Navigation.
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posted on 2023-06-07, 22:26 authored by Patrícia A Vargas, Leandro N de Castro, Roberto Michelan, Fernando J Von ZubenThis paper proposes a non-parametric hybrid system for autonomous navigation combining the strengths of learning classifier systems, evolutionary algorithms, and an immune network model. The system proposed is basically an immune network of classifiers, named CLARINET. CLARINET has three degrees of freedom: the attributes that define the network cells (classifiers) are dynamically adjusted to a changing environment; the network connections are evolved using an evolutionary algorithm; and the concentration of network nodes is varied following a continuous dynamic model of an immune network. CLARINET is described in detail, and the resultant hybrid system demonstrated effectiveness and robustness in the experiments performed, involving the computational simulation of robotic autonomous navigation.
History
Publication status
- Published
ISSN
0302-9743Publisher
ICARISExternal DOI
Page range
69-80Pages
12.0Presentation Type
- paper
Event name
Artificial Immune Systems Second International Conference, ICARIS 2003Event location
Edinburgh, UK.Event type
conferenceEvent date
September 1-3, 2003.ISBN
3-540-40766-9Department affiliated with
- Informatics Publications
Notes
Lecture Notes in Computer Science (LNCS 2787) Special Issue on Artificial Immune SystemsFull text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-02-06Usage metrics
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