author = {Evelina Lamma and Fabrizio Riguzzi and Lu\'\i{}s Moniz Pereira},
  title = {Belief Revision via {L}amarckian Evolution},
  booktitle = {Second International Workshop on Computational Models of Scientific
    Reasoning And Applications (II CMSRA) held at IC-AI 2002 Conference, Monte Carlo
Resort, Las Vegas, Nevada, USA, June 27, 2002},
  editor = {Claudio Delrieux},
  abstract = {We present a genetic algorithm for performing belief revision in
a multi-agent environment. In this setting, different individuals
are exposed to different experiences. This may happen because the
world surrounding an agent changes over time or because  we allow
agents exploring different parts of the world. The algorithm
permits the exchange of chromosomes from different agents and
combines two different evolution strategies, one based on
Darwin's and the other  on Lamarck's evolutionary theory.
Experiments on a problem of digital circuit diagnosis and on the
$n$-queen problem show that the addition of the Lamarckian
operator in the single agent case improves the fitness of the
best solution, even if in the digital circuit case the fitness
difference is not significant. Moreover, the experiments show
that the distribution of constraints, even if it leads to a
decrease of the fitness of the best solution, does not produce a
significant difference.},
  year = {2002},
  publisher = {CSREA},
  address = {Bogart, Georgia, \USA},
  keywords = {Genetic Algorithms,Theory Revision},
  month = jun,
  pages = {1--7},
  http = {http://www.lip.uns.edu.ar/cmsra/lamma.pdf},
  pdf = {http://ml.unife.it/wp-content/uploads/Papers/LamRigPer-CMSRA02.pdf}
  author = {Evelina  Lamma and Giuseppe Modestino and Fabrizio Riguzzi and Sergio Storari
    and Paola Mello and Annamaria Nanetti},
  title = {An Intelligent Medical System for Microbiological Data
    Validation and Nosocomial Infection Surveillance},
  booktitle = {The 15th International Conference on Computer Based Medical Systems
     (CBMS 2002), Maribor, Slovenia, 4-7 June 2002},
  year = {2002},
  publisher = {{IEEE} Press},
  address = {Los Alamitos, California,  \USA},
  pages = {13--20},
  month = jun,
  editor = {Kokol, P. and Stiglic, B. and Zorman, M. and Zazula, D. },
  pdf = {http://ml.unife.it/wp-content/uploads/Papers/LamRigPer-CBMS02.pdf},
  url = {http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1011348&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D1011348},
  doi = {10.1109/CBMS.2002.1011348},
  isbn = {0769516149}
  author = {Marco Alberti and Evelina Lamma},
  title = {Synthesis of Object Models from Partial Models: a {CSP} Perspective},
  booktitle = {Proceedings of the Fifteenth European Conference on Artificial Intelligence (ECAI 2002)},
  pages = {116-120},
  year = {2002},
  editor = {Frank van Harmelen},
  volume = {77},
  series = {Frontiers in Artificial Intelligence and Applications},
  month = {July},
  publisher = {IOS Press},
  abstract = {In this work we present an approach for the synthesis of object models
(expressed as Constraint Satisfaction Problems, CSPs) from views or
partial models (expressed, in their turn, as CSPs as well).

The approach we propose is general enough to consider different types
of features and relationships in the views. This is achieved by
introducing the notion of model representation, where features,
relationships and their domains are expressed. The (complete) model
can be synthesized through a proper algorithm, which provides a
albeling between the (complete) model and the partial models'
components.  The generated CSP representing the synthesized model must
satisfy (or, better, entail) any constraint among features and any
relationship occurring in each partial model. 

The framework is applied for synthesizing object models (i.e., CSP
descriptions).  We provide two basic approaches for synthesizing a
minimal or a correct model, and we experiment them by considering some
case studies in artificial vision.},
  isbn = { 978-1-58603-257-9}

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