This paper studies infinite-horizon stochastic games in which players observe payoffs and noisy public information about a hidden state each period. We find that, very generally, the feasible and individually rational payoff set is invariant to the initial prior about the state in the limit as...

We characterize perfect public equilibrium payoffs in dynamic stochastic games, in the case where the length of the period shrinks, but players' rate of time discounting and the transition rate between states remain fixed. We present a meaningful definition of the feasible and individually...

Blockchains are distributed ledgers, operated within peer-to-peer networks. If reliable and stable, they could offer a new, cost effective way to record transactions, but are they? We model the proof-of-work blockchain protocol as a stochastic game and analyse the equilibrium strategies of...

Discrete-time stochastic games with a finite number of states have been widely applied to study the strategic interactions among forward-looking players in dynamic environments. These games suffer from a “curse of dimensionality” when the cost of computing players’ expectations over all...

We present an algorithm to compute the set of perfect public equilibrium payoffs as the discount factor tends to one for stochastic games with observable states and public (but not necessarily perfect) monitoring when the limiting set of (long-run players') equilibrium payoffs is independent of...

We present an algorithm to compute the set of perfect public equilibrium payoffs as the discount factor tends to one for stochastic games with observable states and public (but not necessarily perfect) monitoring when the limiting set of (long-run players') equilibrium payoffs is independent of...

This paper extends the framework of Kajii and Morris (1997) to study the question of robustness to incomplete information in repeated games. We show that dynamically robust equilibria can be characterized using a one-shot robustness principle that extends the one-shot deviation principle. Using...