In their 1984 paper “Coping with Complexity: The Adaptive Value of Changing Utility” Cohen and Axelrod propose an original way to deal with our cognitive limitations. They suggests that to cope with complexity and to overcome our limited knowledge, motivational change might help. Their paper presents a case in which changing utility is adaptive, that is in which motivational change leads to better outcomes because the agents has wrong or incomplete beliefs.
The proposal has received surprisingly little attention given the deserved fame of its authors. Its approach invites a more interactive reconstruction. For this purpose, I put together a Jupyter notebook using Python3. The notebook is available in my github repo and you also view it here using the Jupyter projects nbviewer. The interactive widgets, however, don’t work in the viewer, so you better explore the notebook in your own Jupyter installation.
I have not made use of the full range of available visualisation tools. In fact, I have hardly scratched the surface and to get a better grasp of Cohen and Axelrod’s proposal one might want to play with the central production function. Nonetheless, I hope the notebook allows a different way to access an overlooked proposal in the debate on how to choose in light of our limited cognitive capacities.