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In addition to providing a concise review of computational models of explanation. This chapter describes a new neural network model that shows how explanations can be performed by multimodal distributed representations. A more psychologically elegant way of performing inference to the best explanation, the model ECHO, is described in the section on neural networks. This chapter provides an over view about Bayesian networks providing an excellent tool for computational and normative philosophical applications. All of the computational models described in this chapter are mechanistic, although they differ in what they take to be the parts and interactions that are central to explaining human thinking; for the neural network approaches, the computational mechanisms are also biological ones. This chapter provides a review about four major computational approaches to understanding scientific explanations: deductive, schematic, probabilistic, and neural network.

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Part IV - Concluding Remarks

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Part IV - Concluding Remarks

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