The novelty of our model is to combine models of collective action on networks with models of social learning. Agents …

content. Using a transfer learning-based machine learning algorithm we convert complex images into lower-level features. This …

We model the spread of news as a social learning game on a network. Agents can either endorse or oppose a claim made in … neighbors' past actions. Given these inputs, agents follow strategies derived via multi-agent deep reinforcement learning and …

The paper analyzes a dynamic model of rational strategic learning in a network. It complements existing literature by … links. This means that in the design of networks there exists a trade-off between the speed of learning and accuracy. …

concerning the role of those characteristics in determining learning, diffusion, decisions, and resulting behaviors. We also …

We study social learning in a social network setting where agents receive independent noisy signals about the truth …

We investigate how the selection process of a leader affects team performance with respect to social learning. We use a … models of social learning to investigate the micro-level mechanisms. We find that overconfidence and conservatism contribute …