AA1*: A Dynamic Incremental Network that Learns by Discrimination

  • Christophe Giraud-Carrier
  • Tony Martinez


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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  1. [1]
    C. Barker and T.R. Martinez. Proof of cor rectness for ASOCS AA3 networks. IEEE Transactions on Systems, Man, and Cybernetics, 24(3):503–510, 1994.CrossRefGoogle Scholar
  2. [2]
    C. Giraud-Carrier and T. Martinez. Using precepts to augment training set learning. In Proc. ANNES′93, 46–51. Google Scholar
  3. [3]
    C. Giraud-Carrier and T. Martinez. Analysis of the convergence and generalization of AA1. JPDC, 1994 (to appear). Google Scholar
  4. [4]
    L.O. Hall and S.G. Romaniuk. A hybrid connectionist, symbolic learning system. In Proc. AAAI′90, 783–788.Google Scholar
  5. [5]
    T.R. Martinez . Adaptive Self-Organizing Networks. PhD thesis, University of California, Los Angeles, 1986.Google Scholar
  6. [6]
    T.R. Martinez. Consistency and gener alization in incrementally trained connectionist networks. In Proc. International Symposium on Circuits and Systems, 706–709, 1990.Google Scholar
  7. [7]
    T.R. Martinez, J.C. Barker, C. Giraud-Carrier. A generalizing adaptive discriminant network. In Proc. WCNN′93, I:613–616Google Scholar
  8. [8]
    T.R. Martinez and D.M. Campbell. A self-adjusting dynamic logic module. JPDC, 11(4):303–313, 1991.Google Scholar
  9. [9]
    T.R. Martinez and D.M. Campbell. A self-organizing binary decision tree for incrementally defined rule based systems. IEEE Transactions on Systems, Man, and Cybem etics, 21(5):1231–1238, 1991.CrossRefGoogle Scholar
  10. [10]
    T.R. Martinez and J.J. Vidal. Adaptive parallel logic networks. JPDC, 5(l):26–58, 1988.Google Scholar
  11. [11]
    P.M. Murphy and D.W. Aha. UCI reposit ory of machine learning databases. University of California, Irvine, Department of Information and Computer Science, 1992.Google Scholar
  12. [12]
    D. Ourston and R. Mooney. Changing the rules: A comp rehensive approach to theory refinement. In Proc. AAAI′90, 815–820.Google Scholar
  13. [13]
    R. Sun. A connectionist model for commensense reasoning incorporating rules and similarities. Knowledge Acquisition, 4:293–321, 1992.CrossRefGoogle Scholar

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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