 There is a long tradition, across psychology, linguistics, and philosophy, in which analogy and metaphor are seen as an important key to abstract reasoning and creativity (Black 1962; Hesse 1943 [1966]; Lakoff &amp; Johnson 1980; Gentner 1982; Lakoff &amp; Turner 1989). Beginning in the 1980s several notable attempts have been made to apply computational tools in order to both understand and generate analogies. Douglas Hofstadter and Melanie Mitchell’s Copycat, developed as a model of high-level cognition, has “codelets” compete within a network in order to answer simple questions of analogy: “abc is to abd as ijk is to what?” (Hofstadter 2008). Holyoak and Thagard envisage metaphors as analogies in which the source and target domain are semantically distinct, calling for relational comparison between two semantic nets (Holyoak &amp; Thagard 1989, 1995; see also Falkenhainer, Forbus, &amp; Gentner 1989). In the Holyoak and Thagard model those comparisons are constrained in a number of different ways that call for coherence; their computational modeling for coherence in the case of metaphor was in fact a direct ancestor to Thagard’s coherence modeling of scientific theory change discussed above (Thagard 1988, 1992).