We propose a framework in order to econometrically estimate case-based learning and apply it to empirical data from … twelve 2 × 2 mixed strategy equilibria experiments. Case-based learning allows agents to explicitly incorporate information …-based learning to other learning models (reinforcement learning and self-tuned experience weighted attraction learning) while using …

local interactions. Amongst others, we discuss best reply learning in a global- and in a local- interaction framework and … best reply learning in multiple location models and in a network formation context. Further, we discuss imitation learning …

Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 × 2 …, payoff-sampling equilibrium, and impulse balance equilibrium) which represent the long-run equilibrium of a learning process …. Secondly, we relate our results to four different learning models (impulse-matching learning, action-sampling learning, self …

Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 × 2 …, payoff-sampling equilibrium, and impulse balance equilibrium) which represent the long-run equilibrium of a learning process …. Secondly, we relate our results to four different learning models (impulse-matching learning, action-sampling learning, self …

affiliation-motivated individuals engaged in game-play. The first model captures learning by motivated agents during strategic …

We propose a framework in order to econometrically estimate case-based learning and apply it to empirical data from … twelve 2 × 2 mixed strategy equilibria experiments. Case-based learning allows agents to explicitly incorporate information …-based learning to other learning models (reinforcement learning and self-tuned experience weighted attraction learning) while using …