We model the spread of news as a social learning game on a network. Agents can either endorse or oppose a claim made in a piece of news, which itself may be either true or false. Agents base their decision on a private signal and their neighbors' past actions. Given these inputs, agents follow...

In this article, we develop a new way to capture knowledge diffusion and assimilation in innovation networks by means of an agent-based simulation model. The model incorporates three essential characteristics of knowledge that have not been covered entirely by previous diffusion models: the...

This book analyses situations in which individual agents, who might be different from each other, interact and produce behaviour on the aggregate level which does not correspond to that of the average actor. This leads to aggregate outcomes which would be impossible to explain in a more standard...