Coping with Complexity: The adaptive value of changing utility

Cohen, Michael D and Axelrod, Robert (1984). Coping with Complexity: The Adaptive Value of Changing Utility American Economic Review, 74 (1), 30-42

I took this paper on particularly because of the authors and because I thought it might be a short version of Harnessing Complexity, their book on using complexity science ideas in organization management. The paper is about management and managing complexity, actually, as per the title. It moves from econometric modeling and implies that even the best models are incomplete because complex organizations always have elements that screw up your model.

They create a model based on an AI model of playing checkers- yes, checkers, I know, it's pointless because we've solved checkers. The AI model for checkers based learning on 'surprise.' If ever a move on the other player's part was unexpected and the algorithm is surprised then there is a change in preferences. The example they start with is how a manager is trying to maximize productivity by choosing the right amount of labor. The manager is assumed to use an inverted parabola as the utility function, after each time period the basic algorithm would adjust a coefficient as it searches for the optimal distribution of labor for productivity.

But there could be things like thievery! The manager did not account for this. So Cohen and Axelrod quantify a measure of surprise, which to me, just feels like a residual from a regression model. They then suggest a dynamic model of adjusting preferences to account for the hidden complexity. The model adjusts preferences, but not too much since it dampens the changes.

I didn't see a terribly large amount of application here. This paper is from 1984 and it is reasonable to expect that improved econometric models have come into vogue since then. The one thing I did like was that "the simple principles underlying the success of the Samuel Checker Player can be transfered with powerful effect to other task domains." The other importance here is that hidden complexity can be something that can be 'coped' with. Perhaps their book, mentioned above, goes much further than that.