Belief Revision by Lamarckian Evolution

  • Evelina Lamma
  • Luís MonizPereira
  • Fabrizio Riguzzi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2037)


We propose a multi-agent genetic algorithm to accomplish belief revision. The algorithm implements a new evolutionary strategy resulting from a combination of Darwinian and Lamarckian approaches. Besides encompassing the Darwinian operators of selection, mutation and crossover, it comprises a Lamarckian operator that mutates the genes in a chromosome that code for the believed assumptions. These self mutations are performed as a consequence of the chromosome phenotype’s experience obtained while solving a belief revision problem. They are directed by a belief revision procedure which relies on tracing the logical derivations leading to inconsistency of belief, so as to remove the latter’s support on the gene coded assumptions, by mutating the genes.


Genetic Algorithm Logic Program Crossover Operator Belief Revision Integrity Constraint 
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 Berlin Heidelberg 2001

Authors and Affiliations

  • Evelina Lamma
    • 1
  • Luís MonizPereira
    • 2
  • Fabrizio Riguzzi
    • 1
  1. 1.Dipartimento di IngegneriaUniversità di FerraraFerraraItaly
  2. 2.Centro de Inteligência Artificial (CENTRIA), Departamento de Informática, Faculdade de Ciências e TecnologiaUniversidade Nova de LisboaCaparicaPortugal

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