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With model uncertainty characterized by a convex, possibly non-dominated set of probability measures, the agent minimizes the cost of hedging a path dependent contingent claim with given expected success ratio, in a discrete-time,…

Mathematical Finance · Quantitative Finance 2017-09-29 Erhan Bayraktar , Gu Wang

The probabilistic modal {\mu}-calculus is a fixed-point logic designed for expressing properties of probabilistic labeled transition systems (PLTS's). Two equivalent semantics have been studied for this logic, both assigning to each state a…

Logic in Computer Science · Computer Science 2015-07-01 Matteo Mio

We introduce a new stochastic duration model for transaction times in asset markets. We argue that widely accepted rules for aggregating seemingly related trades mislead inference pertaining to durations between unrelated trades: while any…

Econometrics · Economics 2020-05-20 Samuel Gingras , William J. McCausland

We develop a probabilistic approach to continuous-time finite state mean field games. Based on an alternative description of continuous-time Markov chain by means of semimartingale and the weak formulation of stochastic optimal control, our…

Probability · Mathematics 2018-08-24 Rene Carmona , Peiqi Wang

The present paper gives a mathematical, in particular, syntax-independent, formulation of intensionality and dynamics of computation in terms of games and strategies. Specifically, we give a game semantics for a higher-order programming…

Logic in Computer Science · Computer Science 2021-02-10 Norihiro Yamada , Samson Abramsky

Optimal behavior in (competitive) situation is traditionally determined with the help of utility functions that measure the payoff of different actions. Given an ordering on the space of revenues (payoffs), the classical axiomatic approach…

General Economics · Economics 2020-04-27 Stefan Rass

We unify and establish equivalence between the pathwise and the quasi-sure approaches to robust modelling of financial markets in discrete time. In particular, we prove a Fundamental Theorem of Asset Pricing and a Superhedging Theorem,…

Mathematical Finance · Quantitative Finance 2019-12-04 Jan Obloj , Johannes Wiesel

Stochastic games are a convenient formalism for modelling systems that comprise rational agents competing or collaborating within uncertain environments. Probabilistic model checking techniques for this class of models allow us to formally…

Logic in Computer Science · Computer Science 2022-11-14 Marta Kwiatkowska , Gethin Norman , David Parker , Gabriel Santos

There are only limited classes of multi-player stochastic games in which independent learning is guaranteed to converge to a Nash equilibrium. Markov potential games are a key example of such classes. Prior work has outlined sets of…

Computer Science and Game Theory · Computer Science 2024-05-15 Fatemeh Fardno , Seyed Majid Zahedi

Consider concurrent, infinite duration, two-player win/lose games played on graphs. If the winning condition satisfies some simple requirement, the existence of Player 1 winning (finite-memory) strategies is equivalent to the existence of…

Logic in Computer Science · Computer Science 2018-05-01 Stephane Le Roux

When testing a statistical hypothesis, is it legitimate to deliberate on the basis of initial data about whether and how to collect further data? Game-theoretic probability's fundamental principle for testing by betting says yes, provided…

Methodology · Statistics 2023-08-30 Glenn Shafer

Several notions of bisimulation relations for probabilistic non-deterministic transition systems have been considered in the literature. We consider a novel testing-based behavioral equivalence called upper-expectation bisimilarity and…

Logic in Computer Science · Computer Science 2013-10-03 Matteo Mio

Game-theoretic characterizations of process equivalences traditionally form a central topic in concurrency; for example, most equivalences on the classical linear-time / branching-time spectrum come with such characterizations. Recent work…

Logic in Computer Science · Computer Science 2025-01-28 Jonas Forster , Lutz Schröder , Paul Wild

We study a class of stochastic dynamic games that exhibit strategic complementarities between players; formally, in the games we consider, the payoff of a player has increasing differences between her own state and the empirical…

Computer Science and Game Theory · Computer Science 2010-12-13 Sachin Adlakha , Ramesh Johari

A long-running difficulty with conventional game theory has been how to modify it to accommodate the bounded rationality of all real-world players. A recurring issue in statistical physics is how best to approximate joint probability…

Statistical Mechanics · Physics 2007-05-23 David H. Wolpert

Definable zero-sum stochastic games involve a finite number of states and action sets, reward and transition functions that are definable in an o-minimal structure. Prominent examples of such games are finite, semi-algebraic or globally…

Optimization and Control · Mathematics 2015-01-05 Jérôme Bolte , Stéphane Gaubert , Guillaume Vigeral

For a game with positive expectation and some negative profit, a unique price exists, at which the optimal proportion of investment reaches its maximum. For a game with parallel translated profit, the ratio of this price to its expectation…

Optimization and Control · Mathematics 2014-11-25 Yukio Hirashita

We study the connection between the Aubry-Mather theory and a mean-field game (MFG) price-formation model. We introduce a framework for Mather measures that is suited for constrained time-dependent problems in R. Then, we propose a…

Analysis of PDEs · Mathematics 2021-09-14 Yuri Ashrafyan , Tigran Bakaryan , Diogo Gomes , Julian Gutierrez

We introduce and study a notion of duality for two classes of optimization problems commonly occurring in probability theory. That is, on an abstract measurable space $(\Omega,\mathcal{F})$, we consider pairs $(E,\mathcal{G})$ where $E$ is…

Probability · Mathematics 2025-07-03 Adam Quinn Jaffe

In this note, we present a novel measure of similarity between two functions. It quantifies how the sub-optimality gaps of two functions convert to each other, and unifies several existing notions of functional similarity. We show that it…

Machine Learning · Computer Science 2025-01-15 Chengpiao Huang , Kaizheng Wang
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