I’ve been thinking about Agent-Based Models (ABM) and how they are employed in thinking about policy and decision-making. My assessment is that that community has only scratched the surface of the possible with respect to modeling, and is currently employing ABM in ways that don’t really accomplish the research goals or potential for exploring micro-macro linkages to the extent possible and necessary.
My view as developed in that post is that debt is central to understanding economic systems, and not just because it has a redistributive element in apportioning losses between creditors and debtors when recession forces credit writedowns. In any event, I think the standard approach of simplifying complex economic systems leads to simplistic models that are inadequate for anyone interested in tail risk.
The White House Big Data Research and Development Initiative addresses the need for data science in the military, biomedicine, computers, and the environment to advance. Read this blog post by Martin LaMonica on Cutting Edge.
Kip Katsarelis is lead producer for the new SimCity game Electronic Arts' Maxis studio is developing. We recently made the trek to Emeryville, Calif., to get a look at the PC game, which is due out in 2013.
"Our new GlassBox engine is very powerful. It’s an agent-based simulation, so we’re tracking every single Sim in the world."
Can your social network make you fat? Affect your mood? Political scientist James H. Fowler reveals the dynamics of social networks, the invisible webs that connect each of us to the other. With Nicholas A Christakis, Fowler recently coauthored, Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives..
The wide adoption of social media has increased the competition among ideas for our finite attention. We employ a parsimonious agent-based model to study whether such a competition may affect the popularity of different memes, the diversity of information we are exposed to, and the fading of our collective interests for specific topics. Agents share messages on a social network but can only pay attention to a portion of the information they receive. In the emerging dynamics of information diffusion, a few memes go viral while most do not. The predictions of our model are consistent with empirical data from Twitter, a popular microblogging platform. Surprisingly, we can explain the massive heterogeneity in the popularity and persistence of memes as deriving from a combination of the competition for our limited attention and the structure of the social network, without the need to assume different intrinsic values among ideas.
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