@misc{cogprints1772,
          volume = {2116},
          editor = {Varol Akman and Paolo Bouquet and Richmond Thomason and Roger Young},
           title = {Learning Appropriate Contexts},
          author = {Bruce Edmonds},
       publisher = {Springer-verlag},
            year = {2001},
           pages = {143--155},
        keywords = {learning, conditions of application, context, evolutionary computing, error},
             url = {http://cogprints.org/1772/},
        abstract = {Genetic Programming is extended so that the solutions being evolved do so in the context of  local domains within the total
problem domain.  This produces a situation where different ?species? of solution develop to exploit different ?niches? of the
problem ? indicating exploitable solutions.  It is argued that for context to be fully learnable a further step of abstraction is
necessary.  Such contexts abstracted from clusters of solution/model domains make sense of the problem of how to identify
when it is the content of a model is wrong and when it is the context.  Some principles of learning to identify useful contexts
are proposed.}
}

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