Intuition, intelligence, data compression
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The main goal of my paper is to argue that data compression is a necessary condition for intelligence. One key motivation for this proposal stems from a paradox about intuition and intelligence. For the purposes of this paper, it will be useful to consider playing board games—such as chess and Go—as a paradigm of problem solving and cognition, and computer programs as a model of human cognition. I first describe the basic components of computer programs that play board games, namely value functions and search functions. I then argue that value functions both play the same role as intuition in humans and work in essentially the same way. However, as will become apparent, using an ordinary value function is just a simpler and less accurate form of relying on a database or lookup table. This raises our paradox, since reliance on intuition is usually considered to manifest intelligence, whereas usage of a lookup table is not. I therefore introduce another condition for intelligence that is related to data compression. This proposal allows that even reliance on a perfectly accurate lookup table can be nonintelligent, while retaining the claim that reliance on intuition can be highly intelligent. My account is not just theoretically plausible, but it also captures a crucial empirical constraint. This is because all systems with limited resources that solve complex problems—and hence, all cognitive systems—need to compress data.
KeywordsIntelligence Intuition Bounded rationality Data compression Complexity theory Chess Go
I have presented versions of this article at the University of Rochester, the University of Cambridge, and the University of Osnabrück. I would like to thank the audiences on these occasions for helpful comments. I am especially grateful for comments and discussions to Scott Aaronson, José Hernández-Orallo, Joachim Horvath, Zeynep Soysal and two anonymous referees for this journal.
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