MCMP Summer School Mathematical Philosophy for Female Students 2017
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Program

Room Arrangement

DateAddress, Room
24.07.2016 Geschwister-Scholl-Platz 1, Senatssaal
25.07. - 29.07.2016 Richard-Wagner-Straße 10, room numbers in program below
30.07.2016 Geschwister-Scholl-Platz 1, Senatssaal

 

 

Sunday, 24 July

TimeTopic
16:00 - 17:00 Registration.
17:00 - 17:15 Welcome.
17:15 - 18:30 Welcome Lecture: What is Mathematical Philosophy? (Stephan Hartmann & Hannes Leitgeb, MCMP).
18:30 Country Taste

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Monday, 25 July

TimeTopic
08:00 - 09:00 Registration.
09:00 - 10:15 Elementary Logic and Probability (Gil Sagi, MCMP). (Room 102)
10:15 - 10:45 Coffee Break.
10:45 - 12:00 Tutorial for 'Elementary Logic and Probability' (Gil Sagi, MCMP). (Room 102)
12:00 - 13:30 Lunch Break.
13:30 - 14:45 Parallel MCMP Fellows' Sessions:

1: Catherine Herfeld: Using Social Network Analysis in Philosophy. (Room 108)
2: Milena Ivanova: Aesthetic Values in Scientific Practise.
(Room 109)
3: Patricia Palacios: Reduction and Emergence in Physics.
(Room 110)
4: Reuben Stern: An Interventionist's Guide to Choice. (Room 101)
14:45 - 15:15 Coffee Break.
15:15 - 16:30 Calculus and Vector and Affine Spaces (Adam Caulton, MCMP). (Room 102)
16:30 - 17:45 Tutorial for 'Calculus and Vector and Affine Spaces' (Adam Caulton, MCMP). (Room 102)

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Tuesday, 26 July

TimeTopic
09:00 - 10:15 Lecture Stream 1: Modeling the Evolution of Behavior (Cailin O'Connor, UCI). (Room 102)
10:15 - 10:45 Coffee Break.
10:45 - 12:00 Tutorial: Modeling the Evolution of Behavior (Cailin O'Connor, UCI). (Room 102)
12:00 - 13:30 Lunch Break.
13:30 - 14:45 Lecture Stream 2: Space, Time, and Geometry from Newton to Einstein, feat. Maxwell (James Weatherall, UCI). (Room 102)
14:45 - 15:15 Coffee Break.
15:15 - 16:30 Tutorial: Space, Time, and Geometry from Newton to Einstein, feat. Maxwell (James Weatherall, UCI). (Room 102)
16:30 - 17:45 Lecture Stream 3: From Epistemic Logic to Social Cognition (Rineke Verbrugge, RUG). (Room 102)

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Wednesday, 27 July

TimeTopic
09:00 - 10:15 Tutorial: From Epistemic Logic to Social Cognition (Rineke Verbrugge, RUG). (Room 102)
10:15 - 10:45 Coffee Break.
10:45 - 12:00 Lecture Stream 1: Modeling the Evolution of Behavior (Cailin O'Connor, UCI). (Room 102)
12:00 - 13:30 Lunch Break.
13:30 - 14:45 Tutorial: Modeling the Evolution of Behavior (Cailin O'Connor, UCI). (Room 102)
14:45 - 15:15 Coffee Break.
15:15 - 16:30 Lecture Stream 2: Space, Time, and Geometry from Newton to Einstein, feat. Maxwell (James Weatherall, UCI). (Room 102)
16:30 - 17:45 Tutorial: Space, Time, and Geometry from Newton to Einstein, feat. Maxwell (James Weatherall, UCI). (Room 102)
19:00 - 20:30 Evening Lecture: Philosophical Reflections on Imposter Syndrome (Katherine Hawley, University of St Andrews). (Senatssaal, Main Building) (Watch the lecture @ LMUcast)

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Thursday, 28 July

TimeTopic
09:00 - 10:15 Lecture Stream 3: From Epistemic Logic to Social Cognition (Rineke Verbrugge, RUG). (Room 101)
10:15 - 10:45 Coffee Break.
10:45 - 12:00 Tutorial: From Epistemic Logic to Social Cognition (Rineke Verbrugge, RUG). (Room 101)
12:00 - 13:30 Lunch Break.
13:30 - 14:45 Parallel Sessions:

Lecture Stream 1: Modeling the Evolution of Behavior (Cailin O'Connor, UCI). (Room 108)
Lecture Stream 2: Space, Time, and Geometry from Newton to Einstein, feat. Maxwell (James Weatherall, UCI). (Room 109)
Lecture Stream 3: From Epistemic Logic to Social Cognition (Rineke Verbrugge, RUG). (Room 101)
15:00 - 16:15 [Optional] Career Workshop (Milena Ivanova, MCMP). (Room 110)

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Friday, 29 July

TimeTopic
09:00 - 10:15 Parallel Sessions:

Lecture Stream 1: Modeling the Evolution of Behavior (Cailin O'Connor, UCI). (Room 108)
Lecture Stream 2: Space, Time, and Geometry from Newton to Einstein, feat. Maxwell (James Weatherall, UCI). (Room 109)
Lecture Stream 3: From Epistemic Logic to Social Cognition (Rineke Verbrugge, RUG). (Room 101)
10:15 - 10:45 Coffee Break.
10:45 - 12:00 Parallel Sessions:

Lecture Stream 1: Modeling the Evolution of Behavior (Cailin O'Connor, UCI). (Room 108)
Lecture Stream 2: Space, Time, and Geometry from Newton to Einstein, feat. Maxwell (James Weatherall, UCI). (Room 109)
Lecture Stream 3: From Epistemic Logic to Social Cognition (Rineke Verbrugge, RUG). (Room 101)
12:00 - 13:30 Lunch Break.
13:30 - 14:45 Parallel Sessions:

Lecture Stream 1: Modeling the Evolution of Behavior (Cailin O'Connor, UCI). (Room 108)
Lecture Stream 2: Space, Time, and Geometry from Newton to Einstein, feat. Maxwell (James Weatherall, UCI). (Room 109)
Lecture Stream 3: From Epistemic Logic to Social Cognition (Rineke Verbrugge, RUG). (Room 101)
14:45 - 15:15 Coffee Break.
15:15 - 16:30 Parallel MCMP Fellows' Sessions:

1: Johanna Wolff: Measurement for Philosophers. (Room 109)
2: Barbara Osimani: Coherence and Confirmation in Probabilistic Causal Inference. (Room 101)
3: Karolina Krzy┼╝anowska: From a Philosophical Theory to an Empirical Study: The Case of Indicative Conditionals. (Room 108)
4: Seamus Bradley: Econophysics and Migrating Models. (Room 110)
16:30 - 17:15 Student Poster Sessions. (Room 021)
19:30 Summer School Dinner (Cafe Reitschule).

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Saturday, 30 July

TimeTopic
09:15 - 09:45 Student Presentation: A Syllogistic Reasoning Theory Based On WeakCompletion Semantics (Ana Alexandra Oliveira da Costa, TU Dresden)
09:45 - 10:15 Student Presentation: Climate Change as a Game with 7.4 Billion Players (Dijana Magdinski, University of Zagreb)
10:15 - 10:45 Coffee Break.
10:45 - 11:15 Student Presentation: Probability in Everettian Quantum Mechanics (Chloé de Canson, University of Cambridge)
11:15 - 11:45 Student Presentation: The Justification of Coarse-Graining in Statistical Mechanics (Katie Robertson, University of Cambridge)
11:45 - 12:00 Wrap up and closing.

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Abstracts

Main Lecture Streams

Modeling the Evolution of Behavior

Cailin O'Connor (University of California, Irvine)

In this course, we will cover modeling techniques from game theory, evolutionary game theory, and related evolutionary modeling from biology and the social sciences. We will begin with the basics of modeling behavior in game and decision theory. We will see how these models can be extended dynamically to explore how behavior evolves via learning, cultural evolution, and natural selection. We will explore how such models can provide explanation, understanding, and prediction in philosophy, the social sciences, and biology.

From Epistemic Logic to Social Cognition

Rineke Verbrugge (University of Groningen)

Epistemic logic is the logic of knowledge: how do you reason about what you know and what others know? This logic seems to be crucial in describing negotiations in economics, parallel processors in computer science and multiagent systems in artificial intelligence. Epistemic logic is also philosophically and technically interesting: it has beautiful semantics. The lectures will deal with the following subjects: axiomatic systems and Kripke semantics for knowledge of multiple actors (agents), beliefs, and group knowledge. One of the main questions of the course will be in which way epistemic logic is an idealisation, and how people actually reason about their own and other people's knowledge and beliefs, both in story situations where different participants have different perspectives and in games. We will report on some experiments about social cognition, with children and adults, and we will discuss how formal philosophy can be useful as a guide for empirical studies.

Space, Time, and Geometry from Newton to Einstein, feat. Maxwell

James Owen Weatherall (University of California, Irvine)

This course begins with a discussion and interpretation of classical space-time structure and Minkowski space-time. In the four specialized lectures, we will discuss (1) Varieties of classical space-time structures and their connection to traditional views in the metaphysics of space and time; (2) The structural relationships between Galilean space-time, Newtonian space-time, and Minkowski space-time; (3) The sense in which Maxwell's equations expressed in either Galilean or Newtonian space-time push you towards Minkowski space-time; and (4) Conventionality of simultaneity.

Public Evening Lecture

Philosophical Reflections on Imposter Syndrome

Katherine Hawley (University of St Andrews)

Ever felt that you don't really deserve to be here, that everyone else is much smarter than you, that you're about to be found out? So-called 'imposter syndrome' creates anxiety, dents confidence, and may even become a self-fulfilling prophecy. On the plus side, it raises a host of fascinating philosophical questions, about evidence and rationality; about belief and emotion; and about talent, luck and effort. I will outline and discuss some of these questions. And I will contrast remedies for imposter syndrome which focus on 'fixing' the anxious individual with remedies which also recognise the importance of our social environment.top

Student Presentation Abstracts

The Justification of Coarse-Graining in Statistical Mechanics

Katie Robertson (University of Cambridge)

There is a traditional puzzle: how can the time-symmetry of the underlying microphysics be reconciled with the timeasymmetry manifest elsewhere? Within statistical mechanics, progress with this puzzle can be made; the irreversible equations of statistical mechanics can be constructed from the reversible equations, using the framework advocated by Zwanzig, Zeh and Wallace. However, this framework uses ‘coarse-graining’, a procedure that has been heavily criticized in the literature for being anthropocentric and illusory. I argue that these objections stem from an unnecessary justification and provide an alternative justification. Time permitting, I’ll discuss a consequence of these considerations, namely that the time-asymmetry in statistical mechanics is weakly emergent.

Probability in Everettian Quantum Mechanics

Chloé de Canson (University of Cambridge)

This paper seeks to provide a coherent way of thinking about probabilities in Everettian Quantum Mechanics, taking into account the relationship between the notions of probability, credence, chance, determinism and uncertainty. The basic argument is the following. EQM, because it is a deterministic theory, cannot accommodate chances. It can however accommodate another objective type of probability, which I call descriptive probability, from which arises credence (and therefore uncertainty) through an analogue of the Principal Principle.
The paper is divided into three short sections. In Section I, I argue that, in all situations described by probabilistic theories, agents are uncertain. I very briefly outline why this is a problem for EQM as it is generally understood. In a nutshell, the problem is the following. Given that EQM is deterministic, an agent knows for certain that all outcomes will obtain in different Everettian branches. A tension then arises as one notices that EQM is probabilistic and yet does not seem to straightforwardly allow for uncertainty.
In Section II, I follow Wilson (2013) in adopting the diverging picture of EQM (as opposed to the splitting picture), on which uncertainty follows naturally. I first present the difference between the two pictures (this is illustrated in the paper with a diagram). On the splitting picture, branches have a segment in common, which splits at measurement. On the diverging picture however, the branches are at no stage numerically identical, but are qualitatively identical prior to, and different post, measurement. I then show how simply uncertainty can be explained in the diverging picture: because worlds are qualitatively identical prior to measurement, the agent has self-locating uncertainty as to which world she is in.
In Section III, I argue that there can be no objective chance in diverging EQM, but that there is nonetheless another type of objective probabilities: descriptive probabilities. I begin by arguing that probabilities in EQM are not chances. This is done very straightforwardly by noticing that the debate about whether chance and determinism are compatible may be reduced to a verbal dispute. I then introduce a distinct account of probabilities, which I call descriptive probabilities, and which I believe is very contentious, and propose it as the correct interpretation of probabilities in EQM. This account bears a lot of resemblance to the finite frequency interpretation of probability. Finally, I show that uncertainty arises naturally from these descriptive probabilities.

Climate Change as a Game with 7.4 Billion Players

Dijana Magdinski (University of Zagreb)

Climate change is undoubtedly one of the greatest challenges humanity faces. To tackle the problem of climate change, both mitigation and adaptation efforts are needed. In this paper, I will focus on climate change mitigation, broadly defined as efforts to reduce or prevent emission of greenhouse gases, from a game-theoretical approach. I will present several climate change games and examine how far their results can be extrapolated to real life situations, what is their practical value and what can we learn from these games in order to successfully mitigate climate change.

Generally speaking, climate change mitigation can be modelled as the public goods game in which players must cooperate in order to avoid the risk of collective loss. If they are successful, everybody benefits. However, cooperation is costly for players and the game has a positive outcome only if most players make sacrifices. This creates a strong incentive to free-ride, that is, to let others pay the cost of avoiding collective risk.

In the context of climate change and its mitigation, game theory is useful in at least four ways. First, climate change presents a complex and complicated situation which game theory can simplify in order to reveal its underlying structure and to improve our understanding of such situation. Second, game theory can give insights as to why our former negotiations regarding climate change failed to produce desirable outcomes. Third, it can help to pinpoint the
conditions necessary to achieve cooperation and, consequently, successful climate change mitigation. Finally, game theory enables us to focus on the social component of climate change, that is, on social interactions among people whose behavior affects climate change and among decision and policy makers. The latter is especially important since in contemporary debates much attention is given to scientific endeavors in fighting climate change (e. g. the problem of scientific uncertainty). However, it should be noted that although good science can help people make right decisions, in the end it is people who make those decisions. Therefore, if we are to successfully mitigate climate change, we need to understand it as a social endeavor as well as understand the science behind it.

A Syllogistic Reasoning Theory Based On WeakCompletion Semantics

Ana Alexandra Oliveira da Costa (TU Dresden)

A recent meta-study shows that the conclusion human reasoners draw in psychological experiments about syllogistic reasoning is neither the conclusion predicted by classical first-order logic nor does in fact currently a cognitive theory exist that does not significantly deviate from the empirical data. In our work we explore the use of weak completion semantics (WCS) to model syllogistic reasoning. We considered WCS because it has been successfully applied to other human reasoning tasks like the suppression task, the selection task, the belief bias effect, to reasoning about conditionals and to spatial reasoning.