Here is a 1984 article on Eurisko: https://aliciapatterson.org/stories/eurisko-computer-mind-it...

From the article we learn Eurisko is more of an example of human machine symbiosis than of AI.

"Thus the final crediting of the win should be about 60/40% Lenat/Eurisko," he wrote, "though the significant point here is that neither party could have won alone. The program came up with all the innovative designs and design rules and recognized the significance of most of these. It was a human observer, however, (the author) who appreciated the rest, and who occasionally noticed errors or flaws in the synthesized design rules which would have wasted inordinate amounts of time before being corrected by Eurisko."

Lenat did not know much about the game and its search space was intractable for the AI. The combination of both was able to come up with unique solutions counter-intuitive to humans.

From a certain perspective, Eurisko could also be viewed as on the path to some next iteration of programming that never quite arrived. That is, programming languages stalled in the 70s, as Alan Kay notes in: http://worrydream.com/EarlyHistoryOfSmalltalk/

A look beyond OOP as we know it today can also be done by thinking about late-binding. Prolog's great idea is that it doesn't need binding to values in order to carry out computations [Col *]. The variable is an object and a web of partial results can be built to be filled in when a binding is finally found. Eurisko [Lenat *] constructs its methods—and modifies its basic strategies—as it tries to solve a problem. Instead of a problem looking for methods, the methods look for problems—and Eurisko looks for the methods of the methods. This has been called "opportunistic programming"—I think of it as a drive for more enlightenment, in which problems get resolved as part of the process.

This higher computational finesse will be needed as the next paradigm shift—that of pervasive networking—takes place over the next five years. Objects will gradually become active agents and will travel the networks in search of useful information and tools for their managers. Objects brought back into a computational environment from halfway around the world will not be able to configure themselves by direct protocol matching as do objects today. Instead, the objects will carry much more information about themselves in a form that permits inferential docking. Some of the ongoing work in specification can be turned to this task [Guttag ][Goguen].

Tongue in cheek, I once characterized progress in programming languages as kind of "sunspot" theory, in which major advances took place about every 11 years. We started with machine code in 1950, then in 1956 FORTRAN came along as a "better old thing" which if looked at as "almost a new thing" became the precursor of ALGOL-60 in 1961. In 1966, SIMULA was the "better old thing," which if looked at as "almost a new thing" became the precursor of Smalltalk in 1972.

Everything seemed set up to confirm the "theory" once more: in 1978 Eurisko was in place as the "better old thing" that was "almost a new thing". But 1983—and the whole decade—came and went without the "new thing". Of course, such a theory is silly anyway—and yet, I think the enormous commercialization of personal computing has smothered much of the kind of work that used to go on in universities and research labs, by sucking the talented kids towards practical applications.

I believe Eurisko operates on very similar principles as PI, which is detailed here:http://bactra.org/reviews/hhnt-induction/ in a fascinating review by Shalizi.

> Unlike the classifier system, which acts on raw binary strings, PI rules and representations are Lisp expressions, and there are more structured representations of concepts, which are however still basically rule clusters. Again unlike the classifier system, which gets new rules by using a genetic algorithm on existing ones, PI has a number of specific inductive mechanisms --- specialization, generalization, abduction, and concept formation --- which are intended to be reminiscent of conscious experience, unlike the GA.

PI was invented by Holland, who is more famously known for his contributions to genetic algorithms and evolutionary computation. Those algorithms were meant to be used in a system like PI and not in the stand alone manner typical of today. Learning Classifier Systems being simplified versions of PI, are probably the closest concept to Eurisko in semi-active use. DreamCoder: https://arxiv.org/abs/2006.08381 is the latest development along this investigatory and very much underexplored path to Machine intelligence.