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The randomization of a complete first order theory T is the complete continuous theory T^R with two sorts, a sort for random elements of models of T, and a sort for events in an underlying probability space. We give necessary and sufficient…

Logic · Mathematics 2013-05-01 Uri Andrews , Isaac Goldbring , H. Jerome Keisler

In the context of reverse mathematics, effective transfinite recursion refers to a principle that allows us to construct sequences of sets by recursion along arbitrary well orders, provided that each set is $\Delta^0_1$-definable relative…

Logic · Mathematics 2021-07-01 Anton Freund

Inference in expressive probabilistic models is generally intractable, which makes them difficult to learn and limits their applicability. Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even…

Machine Learning · Computer Science 2016-11-14 Abram L. Friesen , Pedro Domingos

I survey an array of topics in set theory in the context of a novel class of forcing notions: subcomplete forcing. Subcompleteness was originally defined by Ronald Jensen. I have attempted to make the subject somewhat more approachable to…

Logic · Mathematics 2017-05-02 Kaethe Minden

A class of structures is said to have the homomorphism-preservation property just in case every first-order formula that is preserved by homomorphisms on this class is equivalent to an existential-positive formula. It is known by a result…

Logic in Computer Science · Computer Science 2009-03-08 Anuj Dawar

A first-order theory $T$ is a model-complete core theory if every first-order formula is equivalent modulo $T$ to an existential positive formula; the core companion of a theory $T$ is a model-complete core theory $S$ such that every model…

Logic · Mathematics 2025-12-25 Manuel Bodirsky , Bertalan Bodor , Paolo Marimon

This paper formalizes a widely used dynamical class--replicator-mutator dynamics and Price-style selection-and-transmission--and makes explicit the modeling choices (scale, atomic unit, interaction topology, transmission kernel) that…

Theoretical Economics · Economics 2026-01-13 Murad Farzulla

This work identifies a simple pre-training mechanism that leads to representations exhibiting better continual and transfer learning. This mechanism -- the repeated resetting of weights in the last layer, which we nickname "zapping" -- was…

Machine Learning · Computer Science 2024-10-22 Lapo Frati , Neil Traft , Jeff Clune , Nick Cheney

Promoting a theory with a finite number of terms into an effective field theory with an infinite number of terms worsens simplicity, predictability, falsifiability, and other attributes often favored in theory choice. However, the…

History and Philosophy of Physics · Physics 2013-06-26 James D. Wells

Reinforcement learning for open-ended text generation is constrained by the lack of verifiable rewards, necessitating reliance on judge models that require either annotated data or powerful closed-source models. Inspired by recent work on…

Computation and Language · Computer Science 2026-04-14 Xinda Wang , Zhengxu Hou , Yangshijie Zhang , Bingren Yan , Jialin Liu , Chenzhuo Zhao , Zhibo Yang , Bin-Bin Yang , Feng Xiao

The consistency formula for set theory can be stated in terms of the free-variables theory of primitive recursive maps. Free-variable p. r. predicates are decidable by set theory, main result here, built on recursive evaluation of p. r. map…

General Mathematics · Mathematics 2014-05-16 Michael Pfender

We study methods to obtain the consistency of forcing axioms, and particularly higher forcing axioms. We first force over a model with a supercompact cardinal $\theta>\kappa$ to get the consistency of the forcing axiom for $\kappa$-strongly…

Logic · Mathematics 2024-03-19 David Asperó , Sean Cox , Asaf Karagila , Christoph Weiss

In this paper, we consider the supervised pre-trained transformer for a class of sequential decision-making problems. The class of considered problems is a subset of the general formulation of reinforcement learning in that there is no…

Machine Learning · Computer Science 2024-10-03 Hanzhao Wang , Yu Pan , Fupeng Sun , Shang Liu , Kalyan Talluri , Guanting Chen , Xiaocheng Li

We examine normal form solutions of decision trees under typical choice functions induced by lower previsions. For large trees, finding such solutions is hard as very many strategies must be considered. In an earlier paper, we extended…

Statistics Theory · Mathematics 2018-08-10 Nathan Huntley , Matthias C. M. Troffaes

Recently the second author introduced combinatorial principles that characterize supercompactness for inaccessible cardinals but can also hold true for small cardinals. We prove that the proper forcing axiom PFA implies these principles…

Logic · Mathematics 2010-12-10 Matteo Viale , Christoph Weiß

Machine learning algorithms learn to solve a task, but are unable to improve their ability to learn. Meta-learning methods learn about machine learning algorithms and improve them so that they learn more quickly. However, existing…

Machine Learning · Computer Science 2025-01-28 Calarina Muslimani , Alex Lewandowski , Dale Schuurmans , Matthew E. Taylor , Jun Luo

The resurrection axioms are forcing axioms introduced recently by Hamkins and Johnstone, developing on ideas of Chalons and Velickovi\'c. We introduce a stronger form of resurrection axioms (the \emph{iterated} resurrection axioms…

Logic · Mathematics 2017-04-06 Giorgio Audrito , Matteo Viale

A matrix approach to continuous iteration is proposed for general formal series. It leads, in particular, to an order{to{order iteration of the exponential function, and consequently to an algorithmic approach to tetration. Lower{order…

Mathematical Physics · Physics 2014-10-16 R. Aldrovandi

Classification theory of elementary classes deals with first order (elementary) classes of structures (i.e. fixing a set T of first order sentences, we investigate the class of models of T with the elementary submodel notion). It tries to…

Logic · Mathematics 2009-03-23 Saharon Shelah

This paper introduces a class of objects called decision rules that map infinite sequences of alternatives to a decision space. These objects can be used to model situations where a decision maker encounters alternatives in a sequence such…

Theoretical Economics · Economics 2022-09-12 Bhavook Bhardwaj , Siddharth Chatterjee
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