We outline some results of our current research on developing a methodology for solving problems of spatio-temporal reasoning. We consider classifiers for complex concepts in spatio-temporal reasoning that are constructed hierarchically. We emphasise the fact that the construction of such hierarchical classifiers should be supported by domain knowledge. Approximate reasoning networks (AR networks) are proposed for approximation of reasoning schemes expressed in natural language. Such reasoning schemes are extracted from knowledge bases representing domain knowledge. This approach makes it possible to induce classifiers for complex concepts by constructing them along schemes of reasoning extracted from domain knowledge.
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