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OBADE: cognitive modelling with objects
Author(s) -
Darcel Nelly,
Escarabajal MarieCl.
Publication year - 1988
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.1467-8640.1988.tb00117.x
Subject(s) - computer science , representation (politics) , mental representation , knowledge representation and reasoning , comprehension , cognition , natural language processing , process (computing) , artificial intelligence , task (project management) , object (grammar) , human–computer interaction , programming language , psychology , management , neuroscience , politics , political science , law , economics
We realize a computer simulation of children's reasoning in arithmetic word problem solving. The model parses the terms provided to the system in natural language and, while it performs this task, it tries to build its representation of the described situation by the way that the child elaborates a mental problem representation. This image results from three components: semantic knowledge, text comprehension process, and problem‐solving strategies. We emphasize the adequacy, on one hand, between the knowledge representation and manipulation by an object formalism and, on the other hand, between the structure and the use of knowledge interacting in this application. The specific aspect of our model is that the internal representation is realized in an object‐oriented language whose main properties are accurately exploited. This choice allows one to combine the descriptive characteristics of each piece of knowledge with its implication in the progress of the process. The program is supported by the analysis of individual protocols of some children: they allow us to hypothesize on the way the children modify their problem representation during the solving task. We describe the main objects of the model. Then we simulate on the terms of a problem, the way that the process is driven by expectations of contextually relevant information.