Exploring the Philosophical Dimensions of Network Modeling

Our world is densely interconnected, from the neurons in our brains, to the friendships, and airports. We use network models to deal with this vexing complexity. The ultimate goal of these models is, of course, to provide explanations. Under what conditions do network models provide explanations, what are their unique features, how do they relate to other kinds of scientific explanations, and what are the unique problems that network-based explanations face, are the topics of ongoing and lively debates in philosophy. In this talk, I systematically explore these issues, drawing on examples from neuroscience and ecology, and show how points made in this domain are generalizable to all other areas of science that use network models, including AI.