# Ron Peretz

Lecturer, Economics department, Bar Ilan University, Israel.
CV

## Journal Publications

- Z. Hellman, R. Peretz (available online). Values for Cooperative Games over Graphs and Games with Inadmissible Coalitions,
*Games and Economic Behavior*, forthcoming special issue in honour of Lloyd Shapley.
- Y. Babichenko, S. Barman, R. peretz (2016) Empirical Distribution of Equilibrium Play and Its Testing Application,
*Mathematics of Operations Research* 42 (1), 15-29.
- O. Gossner, P. Hernandez, R. Peretz (2016). The Complexity of Interacting Automata,
**International Journal of Game Theory** 45 (1), 461-496.
- R. Peretz (2015). Effective Martingales with Restricted Wagers,
*Information and Computation* 245, 152-164.
- G. Bavly, R.Peretz (2015). How to Gamble Against All Odds,
*Games and Economic Behavior* 94 (1), 157-168.
- Y. Babichenko, Y. Peres, R. Peretz, P. Sousi, and P. Winkler (2014). Hunter, Cauchy Rabbit, and Optimal Kakeya Sets,
*Transactions of the American Mathematical Society* 366 (10), 5567-5586.
- R. Peretz (2013). Learning Cycle Length through Finite Automata,
*Mathematics of Operations Research* 38 (3), 526-534.
- R. Peretz (2013). Correlation through Bounded Recall Strategies,
**International Journal of Game Theory** 42 (4), 867-890.
- R. Peretz (2012). The Strategic Value of Recall,
*Games and Economic Behavior* 74 (1), 332-351.

## Conference Papers

- Y. Babichenko, S. Barman, and R. Peretz (2014). Simple Approximate Equilibria in Large Games,
*15th ACM conference on Economics and Computation*.
- Y. Babichenko, Y. Emek, M. Feldman, B. Patt-Shamir, R. Peretz, R. Smorodinsky (2017). Stable Secretaries,
*18th ACM conference on Economics and Computation*.

## Work in Progress

We study repeated games in which each player i is restricted to
(mixtures of) strategies that can recall up to ki stages of history. Characterising the set of equilibrium payoffs boils down to identifying the individually rational level of each player. In contrast to the classic folk theorem, in which players have unrestricted recall, punishing a bounded-recall player may involve correlation between the punishers' actions. We quantify this correlation in terms of the average per-stage mutual information between the punishers' actions conditioned on the punishee's recalled history. The amount of correlation is proportional to the ratio between the recall capacities of the punishers and the punishee times the logarithm of the number of actions in the stage game. Our result extends to an arbitrary number of players and to other models of bounded memory.

- The Rate of Innovation Diffusion in Social Networks, with I. Arieli, Y. Babichenko, and P. H. Young.