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Posts by Levin Hornischer

MCMP Summer School for Widening Participation in Mathematical Philosophy - LMU Munich

Still time to apply (⏰March 15): The MCMP organizes again the

Summer School for Widening Participation in Mathematical Philosophy (20-24 July 2026).

Lectures by Dunja Šešelja [Bochum], Xueyin (Snow) Zhang [Berkeley], and Sabina Leonelli [TUM].

www.mathsummer.philosophie.uni-muenchen.de/index.html

1 month ago 2 1 0 0
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In the philosophy lab Hannes Leitgeb is an LMU philosopher and winner of the Leibniz Prize. He investigates truth and rationality and under which conditions artificial intelligence arrives at reasonable decisions.

"In the philosophy lab" - new interview with Professor Hannes Leitgeb (Chair of Logic and Philosophy of Language), here: www.lmu.de/en/newsroom/... #philosophy #mathematics #mathematicalphilosophy

3 months ago 20 8 0 0
Hyperintensionality (Stanford Encyclopedia of Philosophy)

The updated SEP entry on #Hyperintensionality is online!
As the topic has exploded in recent years, might be Daniel and I haven't managed to mention YOUR stuff. Don't be upset: rest assured we've mentioned something intensionally equivalent to that. 😎

plato.stanford.edu/entries/hype...

3 months ago 16 7 0 0
Doctoral Fellow (m/f/x)

PhD opportunities: The MCMP's Chair of Logic and Philosophy of Language (Prof. Hannes Leitgeb) at @lmumuenchen.bsky.social advertises two PhD positions (deadline 7 Feb 2026). See job-portal.lmu.de/jobposting/5...

3 months ago 12 6 0 0
Postdoctoral Fellow (m/f/x)

Postdoc opportunities: The MCMP's Chair of Logic and Philosophy of Language (Prof. Hannes Leitgeb) at @lmumuenchen.bsky.social advertises two Postdoc positions (deadline 31 Jan 2026). See job-portal.lmu.de/jobposting/7...

3 months ago 8 7 0 0
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Robustness and trustworthiness in AI: a no-go result from formal epistemology - Synthese Synthese - A major issue for the trustworthiness of modern AI-models is their lack of robustness. A notorious example is that putting a small sticker on a stop sign can cause AI-models to classify...

New paper in Synthese: 'Robustness and trustworthiness in AI: a no-go result from formal epistemology'

❓When does AI model M, on input x, show behavior φ robustly?
💡In modal logic: M,x⊧□φ
➡️Exposes limit on robustness & trustworthiness

link.springer.com/article/10.1...
philpapers.org/rec/HORRAT-13

3 months ago 12 5 0 0
Kurt Gödel Award 2025 – Kurt Gödel Freundeskreis

Back from Bamberg, Germany, where I was fortunate to receive a shared second prize in the Gödel Award 2025 for my essay "A Stability Interpretation of Gödel"🙏🎉 I use the principle of stability to make sense of Gödel's realism about mathematics and idealism about time.
kurtgoedel.de/kurt-goedel-...

4 months ago 5 0 0 0
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Master in Logic and Philosophy of Science Our Master (MA) program in Logic and Philosophy of Science was founded in October 2012. It is an international MA program of the Faculty of Philosophy, Philosophy of Science and Religious Studies at L...

The 2026 application round for the MA in Logic and Philosophy of Science at @lmumuenchen.bsky.social is now open. Please help us spread the word. www.philosophie.lmu.de/en/study/deg...

5 months ago 14 14 0 0
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Levin Hornischer, Universal Analog Computation: Fraïssé limits of dynamical systems - PhilPapers Analog computation is an alternative to digital computation, that has recently re-gained prominence, since it includes neural networks. Further important examples are cellular automata and differentia...

New preprint: "Universal Analog Computation: Fraïssé limits of dynamical systems"

➡️Via neural nets, analog computation re-gains prominence.
❓It lacks universal machines like digital computation: Can they exist?
💡Using Fraïssé limits from logic, we build universal systems.

philpapers.org/rec/HORUAC

6 months ago 2 0 0 0

Thank you so much, Shawn!

8 months ago 2 0 0 0
The preferences concerning three alternatives (apple, banana, cherries) of three stylized individuals are fed into a stylized neural network. The network outputs a ranking of the three alternatives as the aggregated preference of the group. It selects the top ranked alternative, in this case the apple. In the bottom right, there are two stylized scientists wondering if this network is 'anonymous', 'biased', and 'cycle-free' in its preference aggregation.

The preferences concerning three alternatives (apple, banana, cherries) of three stylized individuals are fed into a stylized neural network. The network outputs a ranking of the three alternatives as the aggregated preference of the group. It selects the top ranked alternative, in this case the apple. In the bottom right, there are two stylized scientists wondering if this network is 'anonymous', 'biased', and 'cycle-free' in its preference aggregation.

New paper in JAIR, with Zoi Terzopoulou: 'Learning How to Vote with Principles: Axiomatic Insights Into the Collective Decisions of Neural Networks'

❓Can neural nets find new voting rules to aggregate preferences?
💡Yes, by optimizing for axioms!

jair.org/index.php/ja...
philpapers.org/rec/HORLHT

8 months ago 5 1 1 0

Very happy to have co-organized our summer school with an amazing team 🥳 Thank you to the speakers and participants alike for making this such a nice event!

8 months ago 3 1 0 0
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Take that, Alan!

9 months ago 4 1 0 0
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So currently our paper is the 2nd most read in Mind. This'd be all good and well, if we hadn't been beaten by... Some bloke's 75 year old stuff. 😎

academic.oup.com/mind/advance...

@levinhornischer.bsky.social @standrewsphil.bsky.social @oupphilosophy.bsky.social

9 months ago 7 1 2 0
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'The Logic of Dynamical Systems Is Relevant' is out!
(Or, How I Stopped Worrying and Learned to Love Relevant Logic Again.)
Download here, Open Access of course:

academic.oup.com/mind/advance...

@levinhornischer.bsky.social @standrewsphil.bsky.social

10 months ago 7 2 2 0
Thousands of small dots in 10 different colors on a white background. Dots with the same color form clusters.

A dot represents an input-label pair ('possible world'). Close-by dots are possible worlds that are similar according to the neural network's reasons structure ('internally similar'). The fact that they form monochromatic clusters means that internally similar worlds typically are also externally similar, i.e., have the same label. In this case, there are 10 labels represented by the 10 colors. So the neural network's reasons structure matches that of the world.

Thousands of small dots in 10 different colors on a white background. Dots with the same color form clusters. A dot represents an input-label pair ('possible world'). Close-by dots are possible worlds that are similar according to the neural network's reasons structure ('internally similar'). The fact that they form monochromatic clusters means that internally similar worlds typically are also externally similar, i.e., have the same label. In this case, there are 10 labels represented by the 10 colors. So the neural network's reasons structure matches that of the world.

New preprint, with Hannes Leitgeb @lmu-mcmp.bsky.social: "Explaining Neural Networks with Reasons".

➡️We propose a new faithful and scalable interpretability method for neural networks.
💡Based on a novel mathematico-philosophical theory of reasons.

arxiv.org/abs/2505.14424
philpapers.org/rec/HORENN

11 months ago 4 2 0 0
The algebra of truth values obtained after iterating 'both' and 'neither' two times. 

It consists of 16 truth values shown as black dots on a white background. Some are connected by solid lines, which indicates that, in the algebra, one is less-or-equal to the other. 

There is a small text next to each node describing the truth-value. For example, the node closest to the bottom left corner says { {0,1}_n, {0} }_n. This is the following truth value: Neither 'neither true nor false' nor 'false'. The other nodes are variations thereof.

The algebra of truth values obtained after iterating 'both' and 'neither' two times. It consists of 16 truth values shown as black dots on a white background. Some are connected by solid lines, which indicates that, in the algebra, one is less-or-equal to the other. There is a small text next to each node describing the truth-value. For example, the node closest to the bottom left corner says { {0,1}_n, {0} }_n. This is the following truth value: Neither 'neither true nor false' nor 'false'. The other nodes are variations thereof.

New paper in Notre Dame J. Formal Logic: 'Iterating Both and Neither: With Applications to the Paradoxes'

❓What if we keep on adding new truth-values 'neither a nor b' and 'both a and b'?
➡️Fun math and fresh ideas for paradoxes!

Paper: doi.org/10.1215/0029...
Preprint: philpapers.org/rec/HORIBA

1 year ago 3 0 0 0
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It's been great fun working on this with @franzberto.bsky.social! Read on if you like dynamical systems and/or logic 🙂

❓What's the logic of perturbation conditionals:
➡️ If we perturb the system into a state where A, it will evolve into a state where B.
💡Surprisingly, it's relevant logic!

1 year ago 6 0 0 0