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We call a group $G$ {\it algorithmically finite} if no algorithm can produce an infinite set of pairwise distinct elements of $G$. We construct examples of recursively presented infinite algorithmically finite groups and study their…

Group Theory · Mathematics 2010-12-09 A. Myasnikov , D. Osin

This note provides a simple example demonstrating that, if exact computations are allowed, the number of iterations required for the value iteration algorithm to find an optimal policy for discounted dynamic programming problems may grow…

Artificial Intelligence · Computer Science 2013-12-25 Eugene A. Feinberg , Jefferson Huang

In this brief paper the probability density of a random real, complex and quaternion determinant is rederived using singular values. The behaviour of suitably rescaled random determinants is studied in the limit of infinite order of the…

Statistical Mechanics · Physics 2009-10-31 Giovanni M. Cicuta , Madan L. Mehta

Given a positive random variable $X$, $X\ge0$ a.s., a null hypothesis $H_0:E(X)\le\mu$ and a random sample of infinite size of $X$, we construct test supermartingales for $H_0$, i.e. positive processes that are supermartingale if the null…

Methodology · Statistics 2021-09-21 Harrie Hendriks

Can a problem undecidable with classical resources be decidable with quantum ones? The answer expected is no; as both being Turing theories, they should not solve the Halting problem - a problem unsolvable by any Turing machine. Yet, we…

Quantum Physics · Physics 2021-12-28 Airin Antony

We generalise the randomness test definitions in the literature for both the Martin-L\"of and Schnorr randomness of a series of binary outcomes, in order to allow for interval-valued rather than merely precise forecasts for these outcomes,…

Probability · Mathematics 2023-12-21 Gert de Cooman , Floris Persiau , Jasper De Bock

Inspired by the theory of desirable gambles that is used to model uncertainty in the field of imprecise probabilities, I present a theory of desirable things. Its aim is to model a subject's beliefs about which things are desirable. What…

Artificial Intelligence · Computer Science 2023-05-12 Jasper De Bock

We construct ensembles of random integrable matrices with any prescribed number of nontrivial integrals and formulate integrable matrix theory (IMT) -- a counterpart of random matrix theory (RMT) for quantum integrable models. A type-M…

Mesoscale and Nanoscale Physics · Physics 2016-05-20 Emil A. Yuzbashyan , B. Sriram Shastry , Jasen A. Scaramazza

This paper defines a new notion of bounded computable randomness for certain classes of sub-computable functions which lack a universal machine. In particular, we define such versions of randomness for primitive recursive functions and for…

Logic in Computer Science · Computer Science 2015-07-01 Sam Buss , Douglas Cenzer , Jeffrey B. Remmel

Given a random sample from a random variable $T$ which is bounded from above, $T\le\tau$ a.s., we define processes that are positive supermartingales if $E(T)\ge\mu$. Such processes are called test martingales. Tests of the supermartingale…

Methodology · Statistics 2018-02-20 Harrie Hendriks

We develop a generic computational model that can be used effectively for establishing the existence of winning strategies for concrete finite combinatorial games. Our modelling is (equational) logic-based involving advanced techniques from…

Logic in Computer Science · Computer Science 2025-12-12 Răzvan Diaconescu

This papers addresses the stock option pricing problem in a continuous time market model where there are two stochastic tradable assets, and one of them is selected as a num\'eraire. It is shown that the presence of arbitrarily small…

Pricing of Securities · Quantitative Finance 2014-10-01 Nikolai Dokuchaev

In Major League Baseball, strategy and planning are major factors in determining the outcome of a game. Previous studies have aided this by building machine learning models for predicting the winning team of any given game. We extend this…

Machine Learning · Computer Science 2025-11-05 Morgan Allen , Paul Savala

Classify simple games into sixteen "types" in terms of the four conventional axioms: monotonicity, properness, strongness, and nonweakness. Further classify them into sixty-four classes in terms of finiteness (existence of a finite carrier)…

Computer Science and Game Theory · Computer Science 2011-07-05 Masahiro Kumabe , H. Reiju Mihara

If we define classical foundational concepts constructively, and introduce non-algorithmic effective methods into classical mathematics, then we can bridge the chasm between truth and provability, and define computational methods that are…

General Mathematics · Mathematics 2007-05-23 Bhupinder Singh Anand

Assuming the obvious definitions (see paper) we show the a decidable model that is effectively prime is also effectively atomic. This implies that two effectively prime (decidable) models are computably isomorphic. This is in contrast to…

Logic · Mathematics 2017-01-31 Peter Cholak , Charlie McCoy

We introduce a model of infinitary computation which enhances the infinite time Turing machine model slightly but in a natural way by giving the machines the capability of detecting cardinal stages of computation. The computational strength…

Logic · Mathematics 2013-10-22 Miha E. Habič

Quantum advantage is notoriously hard to find and even harder to prove. For example the class of functions computable with classical physics actually exactly coincides with the class computable quantum-mechanically. It is strongly believed,…

Quantum Physics · Physics 2015-10-07 Howard Dale , David Jennings , Terry Rudolph

TThe problem is to identify a probability associated with a set of natural numbers, given an infinite data sequence of elements from the set. If the given sequence is drawn i.i.d. and the probability mass function involved (the target)…

Machine Learning · Computer Science 2014-07-14 Paul M. B. Vitanyi , Nick Chater

Discrete choice models are commonly used by applied statisticians in numerous fields, such as marketing, economics, finance, and operations research. When agents in discrete choice models are assumed to have differing preferences, exact…

Methodology · Statistics 2010-06-04 Michael Braun , Jon McAuliffe