Why AM and EURISKO Appear to Work

By D. Lenat, John Seely Brown. 1984

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Citations in the corpus

Deep learning in neural networks: An overview (2014, background): “The partially (un)supervised Automated Mathematician / EURISKO (Lenat, 1983; Lenat and Brown, 1984) continually learns concepts by combining previously learnt concepts.”
Artificial evolution for computer graphics (1991, methodology): “Discovery systems, such as AM, Eurisko, and Cyrano, also utilize a form of mutating lisp programs [14][8].”
Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990–2010) (2010, background): “Lenat’s discovery system EURISKO [41], [42] has a preprogrammed interestingness measure which was observed to become more an more inappropriate (“stagnation” problem) as EURISKO created new concepts from old ones with the help of human intervention.”
CYC: Using Common Sense Knowledge to Overcome Brittleness and Knowledge Acquisition Bottlenecks (1986, methodology): “The final wrinkle we'll mention here is that the precise way two concepts are represented can radically effect how easy it is to find the analogy between them; this is discussed more fully in Lenat and Brown (1984).”
CYC: a large-scale investment in knowledge infrastructure (1995, background): “Therefore, in the early 1980s, when the rest of the world was so enthusiastic about NLU, ML, and AI in general, we were pessimistic [2].”
Web-scale information extraction in knowitall: (preliminary results) (2004, methodology): “Our goal in ontology extension is akin to Doug Lenat’s AM and Eurisko systems [18] that automatically extended their knowledge to new predicates using heuristic search.”