New working paper. Title above, links, abstract, contents and introduction below:
Academia.edu: https://www.academia.edu/164885566/Computation_Chess_and_Language_in_Artificial_Intelligence
SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6319062
ResearchGate: https://www.researchgate.net/publication/401355671_Computation_Chess_and_Language_in_Artificial_Intelligence
Abstract: This paper reexamines the foundations of artificial intelligence by contrasting chess and natural language as paradigmatic domains. Chess, long treated as a benchmark for intelligence, is finite, rule-governed, and geometrically well-defined. It lends itself naturally to symbolic search and evaluation. Natural language, by contrast, operates in an unbounded and geometrically complex reality. Its rules are open-ended, its objectives diffuse, and its domain inseparable from embodied experience. With chess as its premier case – McCarthy: “the Drosophila of AI,” – AI has been guided by a deeper assumption: that the first principles of intelligence reduce to the first principles of computation. Drawing on Miriam Yevick’s distinction between symbolic and neural computational regimes, I propose that intelligence must be understood as operating in a geometrically complex world under finite resource constraints. Embodiment is therefore a formal condition of intelligence, not an incidental feature. Recognizing the structural difference between bounded games and open-ended cognition clarifies both the historical trajectory of AI and the conceptual limits of current systems.
Contents
Introduction: Chess, Language, and Intelligence 3
Chess and Language as Paradigmatic Cases for Artificial Intelligence 5
Three Principles of Intelligence (That Aren't Principles of Computation) 12
Chronology of Chess, Language, and AI 15
Introduction: Chess, Language, and Intelligence
Chess has been a central concern of AI from the beginning. AI researchers didn’t become interested in natural language until the 1970s. Before that computational research on natural language was the domain of computational linguistics (CL), which started with machine translation (of texts from one natural language to another) as its primary problem. Thus we have two different disciplines, AI and CL.
In a sense, AI was fundamentally a philosophical exercise. It was an attempt to demonstrate, in effect, that we could understand the human mind in terms of computation. But rather than advance its philosophical objective through argument, it chose computational demonstration as its mode of expression. Chess became a central concern for two reasons: 1) On the one hand it was widely regarded as exhibiting the pinnacle of human reasoning ability. If we could create a computer program to play a championship game of chess, we could create a computer program that would be capable of cognitive or even perceptual task humans can do. 2) But also, the nature of chess made it well-suited for computational investigation.
The article that opens this working paper – Chess and Language as Paradigmatic Cases for Artificial Intelligence – concentrates on this and then goes on to make the point that language is utterly unlike chess in this respect. The chess domain is bounded and well-defined. Natural language is not; it is ill-defined and unbounded.
That’s as far as I got in the article, but I had been aiming for an argument that AI is still, in effect, mesmerized by the chess paradigm. I didn’t make it that far because language is so obviously different from chess that it is difficult to see how anyone would made that mistake.
What I have come to realize, only after I’d finished the article, is that it isn’t so much chess that has mesmerized AI. Rather it is computation itself. AI has been implicitly assuming that the First Principles of intelligence reduce to the First Principles of Computing. The first principles of computing can be found in the work of Alan Turing (the abstract idea of computing) and and others.
The first principles of intelligence are more stringent. As Claude put it a recent dialog:
First principle of intelligence: Must operate in unbounded, geometrically complex physical reality with finite resources.
Those two qualifications, an unbounded, geometrically complex reality, and finite computational resources, change the nature of the problem considerably. I note, in passing, that this allows us to assign formal significance to the concept of embodiment, for it is embodiment that commits intelligence to operating with finite resources in a geometrically complex universe.
Miriam Yevick’s 1975 paper, “Holographic or Fourier Logic,” is the crucial document, but it’s been forgotten. Using identification in the visual domain as her case, she showed that, where we are dealing with geometrically simple objects, sequential symbolic processing is the most efficient computational regime. But when we are dealing with geometrically complex objects, neural net processing is the most efficient computational regime. AI started out with symbolic processing in the 1950s and arrived at neural nets in the 2010s. But it hasn’t explicitly recognized that one must fit the mode of processing to the nature of the world. In that (perhaps a bit peculiar) sense, the researchers in the currently-dominant paradigm don’t know what they’re doing.
The second article in this working paper, Three Principles of Intelligence (That Aren't Principles of Computation), discusses this in more detail. I had it generated by Claude 4.5 after a long series of dialogs over several days.
The last article is a chronology of events in the history of chess and language in AI.
BB; "I propose that intelligence must be understood as operating in a geometrically complex world under finite resource constraints. Embodiment is therefore a formal condition of"...
ReplyDeleteBloody geometry. Everywhere now!.. "an unbounded, geometrically complex reality, and finite computational resources, change the nature of the problem considerably. I note, in passing, that this allows us to assign formal significance to the concept of embodiment, for it is embodiment that commits intelligence to operating with finite resources in a geometrically complex universe."
Also in, a newly discovered use of geometry... of... bubbles...
"Without the simulations, “we could never have thought that [this process] is controlled by geometry,” Priya said.
"They asked the computational scientist Daniel Santos-Oliván on Torres-Sánchez’s team to develop simulations of beating hearts, which revealed that the gaps in the cardiac jelly were indeed fractures. The model showed that as the heart pulses and takes shape, strain concentrates in the outer curvature, stretching and contracting the jelly scaffold so much that it thins, weakens, and eventually breaks. Sensing those fractures, heart muscle cells at the outer curvature then peel away from the heart wall and fall into the jelly’s newly formed cracks, where they seed the trabeculae. Without the simulations, “we could never have thought that [this process] is controlled by geometry,” Priya said."
...
From; "Break It To Make It: How Fracturing Sculpts Tissues and Organs
By CLARE WATSON February 27, 2026
"Growing tissues can crack, break, and dissociate to form structures that can later withstand immense forces.
https://www.quantamagazine.org/break-it-to-make-it-how-fracturing-sculpts-tissues-and-organs-20260227/
SD
Turing must have been one of the most frustrated humans on the planet. Never seeing Turochamp implemented. And using his running advantage as an ELO flattening device to create run around the house chess.[2]
ReplyDeleteI wonder about some of the AI gods of today and their weird, wacky, malevolent or personal incentives to create our current crop of AI.
"Nobody was willing to play it (for some reason, runners are not interested in chess, and chess players do not run). Turing did not give up. He came up with the idea to create a program to play chess and defeat his colleagues. At the time, the computer was at its beginnings. Turing created the first chess program called Turochamp in 1948. His idea was that if I couldn’t beat you, I would make a program that would do that. This second plan was much better. It led to a challenge between man and machine." [2]
"The first principles of computing can be found in the work of Alan Turing (the abstract idea of computing) and and others." ... "Chess has been a central concern of AI from the beginning."...
"Turochamp is a chess programdeveloped by Alan Turing and David Champernowne in 1948."
...
"The resulting recreation was presented at the Alan Turing Centenary Conference on 22–25 June 2012, in a game with chess grandmaster and former world champion Garry Kasparov.[22]Kasparov won the game in 16 moves, and complimented the program for its place in history and the "exceptional achievement" of developing a working computer chess program without being able to ever run it on a computer.[23]"
https://en.wikipedia.org/wiki/Turochamp
[2] What?!
"Run around the house and chess in Bucharest
Adrian Matei Chess, running May 12, 2022
"During WWII, while working in Bletchley Park to break the Enigma code, Alan Turing invented a game that combined chess and running. The contest rules: You sit with your opponent in front of a chess table. You make your move and run around the house. The other player has to move before you return. Once you sit down at the table, the other player runs around the house. Then you have to move, etc. You lose if you are checkmated or fail to move before your opponent returns to his chair.
"The above mentioned is a rare example of a game that exercises both mind and muscles hard. But what made Turing invent such a strange game?
...
https://adimatei.com/2022/05/12/run-around-the-house-and-chess-in-bucharest/
SD
How delightfully odd. What's the cliché? Ah, "truth is stranger than fiction."
Delete