Collective Accuracy: Agent Based & Emergent vs Statistical and Assumed

12/11/14 • 81 min

Center for Advanced Studies (CAS) Research Focus Reduction and Emergence

In the past two decades, agent-based models (ABMs) have become ubiquitous in philosophy and various sciences. ABMs have been applied, for example, to study the evolution of norms and language, to understand migration patterns of past civilizations, to investigate how population levels change in ecosystems over time, and more. In contrast with classical economic models or population-level models in biology, ABMs are praised for their lack of assumptions and their flexibility. Nonetheless, many of the methodological and epistemological questions raised by ABMs have yet to be fully articulated and answered. For example, there are unresolved debates about how to test (or "validate") ABMs, about the scope of their applicability in philosophy and the sciences, and about their implications or our understanding of reduction, emergence, and complexity in the sciences. This conference brings together an interdisciplinary group of researchers aimed at understanding the foundations of agent-based modeling and how the practice can inform and be informed by philosophy. | Center for Advanced Studies & Munich Center for Mathematical Philosophy: 11.12.2014 | Speaker: Scott Page

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Chaos beyond the Butterfly Effect

The sensitive dependence on initial condition associated with chaotic models, the so-called "Butterfly Effect", imposes limitations on the models’ predictive power. These limitations have been widely recognized and extensively discussed. In this lecture, Roman Frigg will draw attention to an additional so far under-appreciated problem, namely structural model error (SME). If a nonlinear model has only the slightest SME, then its ability to generate useful prediction is lost. This puts us in a worse epistemic situation: while we can mitigate against the butterfly effect by making probabilistic predictions, this route is foreclosed in the case of SME. Roman Frigg will discuss in what way the description of problems affects actual modeling projects, in particular in the context of making predictions about the local effects of climate change. | Center for Advanced Studies & Munich Center for Mathematical Philosophy: 10.01.2014 | Speaker: Dr. Roman Frigg

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The Formation of Epistemic Networks

One important area of study for social epistemology is the social structure epistemic groups -- who communicates their knowledge with whom? Significant research has been done on better and worse communication networks, but less has been done on how a group comes to have one network or another. In this talk, I will present a number of results (some recent) from economics and philosophy about how individuals choose with whom to communicate. Understanding how individuals decide where to gain information can help us to design institutions that lead to epistemically more reliable groups. | Center for Advanced Studies & Munich Center for Mathematical Philosophy: 12.12.2014 | Speaker: Kevin Zollmann