During a brainstorming discussion with a colleague on the value of entropy in machine learning models, specifically the models used in threat intelligence work, I mentioned that many of the threat intelligence models in use today seem to overemphasize the pattern recognition aspect of threat intelligence through the egregious use of algorithms. By contrast, they seem to underemphasize the novelty of such aspects as intuition and chaos, both of which would be present if two malicious actors were pitted against a defensive system that is nothing more than an artificially intelligent system with lots of machine learning algorithms. Then I thought about the game of chess, which cognitive psychologists have studied with great interest for more than 70 years. I did a bit of my own research to see what aspects of chess psychologists found most intriguing, and whether any of their findings could be used to build better threat intelligence programs.
The Chess Experiments
The 1965 book Thought and Choice in Chess, by Adriaan D de. Groot, seems to have laid the foundation for the study of psychology in chess. There are several other psychologists who studied the game and its players; William Chase, Herbert Simon and Dr. Ferdinand Gobet are worth mentioning. The short synopsis of their combined research on the best chess players is as follows:
They can almost immediately determine the problem with the position of a piece on the board when shown a picture or a diagram of a random chess game.
They can recognize important features in a position quickly, whether in a picture or on the board in front of them.
They can recall patterns in a position or group of pieces and rapidly come up with moves or countermoves.
They can build mental templates of about 10 pieces and the s ..
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