We study extrapolation between games in a laboratory experiment. Participants in our experiment first play either the dominance solvable guessing game or a Coordination version of the guessing game for five rounds. Afterwards they play a 3x3 normal form game for ten rounds with random matching...

We report the findings of an experiment designed to study how people learn and make decisions in network games. Network games offer new opportunities to identify learning rules, since on networks (compared to e.g. random matching) more rules differ in terms of their information requirements. Our...

This paper studies the learning process carried out by two agents who are involved in many games. As distinguishing all games can be too costly (require too much reasoning resources) agents might partition the set of all games into categories. Partitions of higher cardinality are more costly. A...

In a novel experimental design we study public good games with dynamic interdependencies. More precisely, each agent's income at the end of a period serves as her endowment in the following period. In this setting growth and inequality arise endogenously allowing us to address new questions...

We conduct a laboratory experiment and provide evidence of learning spillovers within and across equivalence classes of “structurally similar” games. These spillovers are inconsistent with existing theories of learning in games.

We present a model of adaptive economic agents who are k periods forward looking. Agents in our model are randomly matched to interact in finitely repeated games. They form beliefs by learning from past behavior of others and then best respond to these beliefs looking k periods ahead. We...

I present and study an evolutionary model of immigration and culturaltransmission of social norms in a set-up where agents are repeatedly matchedto play a one-shot interaction prisoner´s dilemma. Matching can be non-randomdue to limited integration (or population viscosity). The latter refers...

In this paper we provide a framework to reason about limited awareness of the action space in finitely repeated games. Our framework is rich enough to capture the full strategic aspect of limited awareness in a dynamic setting, taking into account the possibility that agents might want to reveal...

In this paper we study learning procedures when counterfactuals (payo s of not-chosen actions) are not observed. The decision maker reasons in two steps: First, she updates her propensities for each action after every payo experience, where propensity is de ned as how much she prefers each...