Arthur Dolgopolov


Dynamic games, Automata, Experimental economics

Economist, Max Weber post-doctoral fellow at European University Institute (EUI)

I work on dynamic games, market games and other problems with big, complex and interesting strategy spaces. I use dynamic programming, non-linear optimization, revealed preference and economic experiments.


Current CV

(Updated September 2020)


Reconstructing Strategies in Dynamic Games

How to correctly estimate strategies of players by only looking at the results of their repeated interactions?

In this paper, we propose an algorithm to reconstruct strategies out of the observed sequence of play in repeated games. The algorithm also accounts for the possibility of measurement and decision making errors, stays agnostic about equilibrium restrictions, and requires only minimal ex ante assumptions. No limited strategy set needs to be assumed.

We show that players use strategies of memory one in experiments, that players do use non-obvious strategies in many games (e.g. Tease-for-tat), and confirm that Australian gas stations learn to collude using the day of the week as coordination device.