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This article is an edited transcript of a lecture given at IJCAI-99, Stockholm, Sweden on 4 August 1999. The article summarizes concepts, principles. and tools that were found useful in applications involving causal modeling. The principles are based on structural-model semantics in which functional (or counterfactua), relationships representing autonomous physical processes are the fundamental building blocks. The article presents the conceptual basis of this semantics, illustrates its application in simple problems and discusses its ramifications to computational and cognitive problems concerning causation.