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Computational Methods in Philosophy

Date: April 11th, 2014
Time: 14:00 – 17:30
Location: Geschwister-Scholl-Platz 1, Room A 120 (PDF, 673 kb)

Recently, computational methods have become an important tool in philosophy of science, epistemology, and value theory. For example, computer simulations have been used to address several central philosophical topics including (1) the evolution of language, (2) paradigm shifts and discovery within scientific communities, (3) the emergence of social norms and morality, and more. In this event, we plan to showcase research by current faculty, students, and visitors at the Munich Center for Mathematical Philosophy (MCMP) who employ computational methods. We also hope to stimulate interest in the methodology of such computational methods and to encourage collaboration among philosophers and scientists working in this area.

Schedule

TimeEvent
14:00 Conor Mayo-Wilson: Introductory Remarks
14:10 - 15:15 Kevin Zollman: Computer Simulation: A Tool for the Philosopher
15:15 - 15:30 Coffee Break
15:30 - 15:50 Will Nalls: The Impact of Deception on Learning in Signaling Games
15:50 - 16:10 Berta Grimau: Empathy versus Punishment in the Evolution of Fairness
16:10 - 16:30 Soroush Rafiee Rad: Voting, Deliberation and Truth
16:30 - 16:50 Hannah Übler: Simulating the Emergence of Norms
16:50 Conor Mayo-Wilson: Concluding Remarks

Abstracts

Computer Simulation: A Tool for the Philosopher

Kevin Zollman, Professor at  Carnegie Mellon University

While other sciences have been quick to adopt computational methods, philosophy has resisted. In this talk I will argue that rather than being a radical new methodology, computer simulations are entirely consistent with traditional philosophical argument. A number of common objections to computer simulations will be discussed, and some advice regarding best practices in simulation will be provided.top

The Impact of Deception on Learning in Signaling Games

William Nalls, MA Candidate at the MCMP

It does not require much examination to decide that deception (or misinformation for that matter) is harmful to an effective exchange of information. However, determining precisely how and to what degree deception harms the exchange of information is not a trivial matter. Zollman et. al. (2013) explore explanations of how effective communication can persist despite the presence of deception, and Godfrey-Smith et. al. (2013) show that common interest can account for informative signaling when there is incentive to deceive. Both of these investigations examine the role of deception in an established signaling system – but might deception impede the development of a signaling system to begin with? I argue that deception does slow down the learning of signaling systems, but does not stop it altogether. In some sense, this is a mark against the ‘costly signaling theory’. The emergence of a signaling system in the presence of deception can be explained without any recourse to the costs of signaling, which seems to indicate that the maintenance of effective communication in the presence of deception could also be explained without such recourse.top

Empathy versus Punishment in the Evolution of Fairness

Berta Grimau, MA Candidate at the MCMP

In this paper, I study the effects of empathy and punishment on the emergence of fairness in bargaining games. Employing tools from evolutionary game theory, I show that, under two plausible definitions of empathy and punishment, empathy plays a substantive role in the emergence of fairness, whereas punishment does not.top

Voting, Deliberation and Truth

Soroush Rafiee Rad, Postdoc at the MCMP and PhD candidate at Tilburg University

There are various ways to reach a group decision on a yes-no question. One way is to vote and decide what the majority votes for. This procedure receives some epistemological support from the Condorcet Jury Theorem. Alternatively, the group members may prefer to deliberate and will eventually reach a decision that everybody endorses -- a consensus. While the latter procedure has the advantage that it makes everybody happy (as everybody endorses the consensus), it has the disadvantage that it is difficult to implement, especially for larger groups. What is more, a deliberation is easy to bias as those group members who make others change their mind may not necessarily be the best truth-trackers themselves. But even if no such biases are present, the consensus may be far away from the truth. And so we ask: When is deliberation a better method to track the truth than simple majority voting? To address this question, we propose a Bayesian model of rational non-strategic deliberation and compare it to the straightforward voting procedure.top

Simulating the Emergence of Norms

Hannah Übler, MA Candidate at the MCMP

It is an everyday experience that people in social groups act accordingly to certain norms. Unlike formal rules or social norms which usually guide our behaviour in terms of what we should do in view of the greater good, a descriptive norm is not essential in any sense for our social coexistence but informs us about how group members commonly behave in certain situations. Using agent-based modelling, Muldoon et al. (2013, 2014) investigated why and how descriptive norms might emerge in a social context. We present some extensions to these models. Additionally, we propose different social settings in which the emergence of (descriptive) norms could be studied, whereby we want to focus on the phenomenon of 'pluralistic ignorance’.