It contends that the notions of analogy and fluidity are fundamental to explain how the human mind solves problems and to create computer programs that show intelligent behavior.

Upon publication, Jon Udell, a BYTE senior technical editor-at-large said:[2] Fifteen years ago, Gödel, Escher, Bach: An Eternal Golden Braid exploded on the literary scene, earning its author a Pulitzer prize and a monthly column in Scientific American.

Douglas Hofstadter's exuberant synthesis of math, music, and art, and his inspired thought experiments with "tangled hierarchy," recursion, pattern recognition, figure/ground reversal, and self-reference, delighted armchair philosophers and AI theorists.

These programs work in stripped-down yet surprisingly rich microdomains.On April 3, 1995, Fluid Concepts and Creative Analogies became the first book ordered online by an Amazon.com customer.

He discusses breadth-first and depth-first techniques, but eventually concludes that the results represent expert systems that incarnate a lot of technical knowledge but don't shine much light on the mental processes that humans use to solve such puzzles.

Instead he devised a simplified version of the problem, called SeekWhence, where sequences are based on very simple basic rules not requiring advanced mathematical knowledge.

The constituent elements of Jumbo are the following: A "temperature" is associated to the present state of the cytoplasm; it determines how probable it is that a destructive codelet is executed.

Numbo is a program by Daniel Defays that tries to solve numerical problems similar to those used in the French game "Le compte est bon".

The program is modeled on Jumbo and Copycat and uses a permanent network of known mathematical facts, a working memory in the form of a cytoplasm, and a coderack containing codelets to produce free associations of bricks in order to arrive at the result.

The chapter subtitle A Critique of Artificial-intelligence Methodology indicates that this is a polemical article, in which David Chalmers, Robert French, and Hofstadter criticize most of the research going on at that time (the early '80s) as exaggerating results and missing the central features of human intelligence.

Some of these AI projects, like the structure mapping engine (SME), claimed to model high faculties of the human mind and to be able to understand literary analogies and to rediscover important scientific breakthroughs.

In the introduction, Hofstadter warns about the Eliza effect that leads people to attribute understanding to a computer program that only uses a few stock phrases.

The authors claim that the input data for such impressive results are already heavily structured in the direction of the intended discovery and only a simple matching task is left to the computer.

Another of Hofstadter's students, Robert French, was assigned the task of applying the architecture of Copycat to a different domain, consisting in analogies between objects lying on a table in a coffeehouse.

AARON, a computer artist that can draw images of people in outdoor settings in a distinctive style reminiscent of that of a human artist; criticism: the program doesn't have any understanding of the objects it draws, it just uses some graphical algorithms with some randomness thrown in to generate different scenes at every run and to give the style a more natural feel.

Although some of the prose generated by the program is quite impressive, due in part to the Eliza effect, the computer does not have any notion of plot or of the meaning of the words it uses.

Another mathematical program, called Geometry, was celebrated for making an insightful discovery of an original proof that an isosceles triangle has equal base angles.

However, he criticises the use that is made of it at present: it encourages the development of fancy[peacock prose] natural-language interfaces instead of the investigation of deep cognitive faculties.