AA1*: A Dynamic Incremental Network that Learns by Discrimination

  • Christophe Giraud-Carrier
  • Tony Martinez
Conference paper


An incremental learning algorithm for a special class of self-organising, dynamic networks is presented. Learning is effected by adapting both the function performed by the nodes and the overall network topology, so that the network grows (or shrinks) over time to fit the problem. Convergence is guaranteed on any arbitrary Boolean dataset and empirical generalisation results demonstrate promise.


Training Instance Negative Instance Node Selection Binary Decision Tree Node Table 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag/Wien 1995

Authors and Affiliations

  • Christophe Giraud-Carrier
    • 1
  • Tony Martinez
    • 2
  1. 1.Department of Computer ScienceUniversity of BristolBristolUK
  2. 2.Department of Computer ScienceBrigham Young UniversityProvoUSA

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