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The vision of machines autonomously carrying out substantive conjecture generation, theorem discovery, proof discovery, and proof verification in mathematics and the natural sciences has a long history that reaches back before the development of automatic systems designed for such processes. While there has been considerable progress in proof verification in the formal sciences, for instance the Mizar project’ and the four-color theorem, now machine verified, there has been scant such work carried out in the realm of the natural sciences—until recently. The delay in the case of the natural sciences can be attributed to both a lack of formal analysis of the so-called “theories” in such sciences, and the lack of sufficient progress in automated theorem proving. While the lack of analysis is probably due to an inclination toward informality and empiricism on the part of nearly all of the relevant scientists, the lack of progress is to be expected, given the computational hardness of automated theorem proving; after all, theoremhood in even first-order logic is Turing-undecidable. We give in the present short paper a compressed report on our building upon these formal theories using logic-based AI in order to achieve, in relativity, both machine proof discovery and proof verification, for theorems previously established by humans. Our report is intended to serve as a springboard to machine-produced results in the future that have not been obtained by humans.

DOI: 10.1007/s11229-014-0424-3

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