I examine the generalizability of a broad range of prominent learning models in explaining contribution patterns in repeated linear public goods games. Experimental data from twelve previously published papers are considered in testing several learning models in terms of how accurately they...

Previous research has shown that opportunities for two-sided partner choice in finitely repeated social dilemma games can promote cooperation through a combination of sorting and opportunistic signaling, with late period defections by selfish players causing an end-game decline. How such...

Previous research has shown that opportunities for two-sided partner choice in finitely repeated social dilemma games can promote cooperation through a combination of sorting and opportunistic signaling, with late period defections by selfish players causing an end-game decline. How such...

This study investigates a potential mechanism to promote coordination. With theoretical guidance using a belief-based learning model, we conduct a multi-period, binary-choice, and weakest-link laboratory coordination experiment to study the effect of gradualism - increasing the required levels...

We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious play, imitation, reinforcement learning, and a trial...

We study beliefs and choices in a repeated normal-form game. In addition to a baseline treatment with common knowledge of the game structure and feedback about choices in the previous period, we run treatments (i) without feedback about previous play, (ii) with no information about the...

In this paper we introduce four new learning models: impulse balance learning, impulse matching learning, action-sampling learning, and payoff-sampling learning. With this models and together with the models of self- tuning EWA learning and reinforcement learning, we conduct simulations over 12...

We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious play, imitation, reinforcement learning, and a trial...

In this paper, we introduce two new learning models: impulse-matching learning and action-sampling learning. These two models together with the models of self-tuning EWA and reinforcement learning are applied to 12 different 2 x 2 games and their results are compared with the results from...