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

Is it possible to develop a confirmation theory for agent-based models? The are good reasons to be skeptical: Classical confirmation theory explains how empirical evidence bears on the truth of hypotheses and theories, while agent-based models are almost always idealized and hence known to be false. Moreover, classical ideas about confirmation have been developed for relatively simple hypotheses, while even the simplest agent-based models have thousands of variables. Nevertheless, we can draw on ideas from confirmation theory in order to develop an account of agent-based model confirmation. Theorists can confirm hypotheses about model/world relations, and they can also use a variety of techniques to investigate the reliability of model results. This paper is an exploration of these possibilities. | Center for Advanced Studies & Munich Center for Mathematical Philosophy: 13.12.2014 | Speaker: Michael Weisberg

One general problem faced by attempts to explain the origins of morality using traditional rational choice theory is that the demands of rationality and the demands of morality often fail to coincide. This can happen in at least three different ways. Sometimes our moral intuitions recommend actions which are identified as irrational (such as cooperating in the prisoner's dilemma or in the centipede game, or rejecting unfair offers in the ultimatum game). Sometimes our moral intuitions recommend an act which is only one of several recognised as rational (as can happen in games having multiple Nash equilibria). And sometimes we have multiple competing moral intuitions in cases where rationality recommends a unique act (such as in asymmetric bargaining games, in contrast to the Nash solution). In this talk, I present a number of results drawn from agent-based models of imitative learning on social networks, showing how this single framework manages to explain many of our moral intuitions across a wide variety of diverse cases. | Center for Advanced Studies & Munich Center for Mathematical Philosophy: 13.12.2014 | Speaker: Jason McKenzie Alexander

Despite ubiquity and universality, norms are still awaiting for a general comprehensive theory. In the presentation, a conceptual, theoretical, and computational framework will be proposed to provide a general account of norms, enabling us to investigate: (a) differences and commonalities among social, moral, and legal norms; (b) norm emergence and change; (c) the individual properties involved or responsible for bringing about norms. The main thesis is that observable conformity is only the tip of the normative iceberg, and that norms cannot emerge in society if they do not previously immerge in the mind, i.e. if they are not first converted into mental representations of some sort. | Center for Advanced Studies & Munich Center for Mathematical Philosophy: 12.12.2014 | Speaker: Rosaria Conte

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

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

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