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Classical probability theory is formulated using sets. In this paper, we extend classical probability theory with propositional computability logic. Unlike other formalisms, computability logic is built on the notion of events/games, which…

Artificial Intelligence · Computer Science 2020-06-23 Keehang Kwon

We consider the synthesis of control policies for probabilistic systems, modeled by Markov decision processes, operating in partially known environments with temporal logic specifications. The environment is modeled by a set of Markov…

Logic in Computer Science · Computer Science 2012-03-07 Tichakorn Wongpiromsarn , Emilio Frazzoli

We introduce Parametric Linear Dynamic Logic (PLDL), which extends Linear Dynamic Logic (LDL) by temporal operators equipped with parameters that bound their scope. LDL itself was proposed as an extension of Linear Temporal Logic (LTL) that…

Logic in Computer Science · Computer Science 2015-12-08 Peter Faymonville , Martin Zimmermann

We propose a new method for optimistic planning in infinite-horizon discounted Markov decision processes based on the idea of adding regularization to the updates of an otherwise standard approximate value iteration procedure. This…

Machine Learning · Computer Science 2023-06-16 Antoine Moulin , Gergely Neu

This paper proposes new semantics for nondeterministic program execution, replacing the standard relational semantics for propositional dynamic logic (PDL). Under these new semantics, program execution is represented as fundamentally…

Logic in Computer Science · Computer Science 2018-03-23 Adam Bjorndahl

Many representation schemes combining first-order logic and probability have been proposed in recent years. Progress in unifying logical and probabilistic inference has been slower. Existing methods are mainly variants of lifted variable…

Artificial Intelligence · Computer Science 2012-02-20 Vibhav Gogate , Pedro Domingos

This paper investigates the motion planning of autonomous dynamical systems modeled by Markov decision processes (MDP) with unknown transition probabilities over continuous state and action spaces. Linear temporal logic (LTL) is used to…

Machine Learning · Computer Science 2022-01-25 Mingyu Cai , Mohammadhosein Hasanbeig , Shaoping Xiao , Alessandro Abate , Zhen Kan

We design temporal description logics suitable for reasoning about temporal conceptual data models and investigate their computational complexity. Our formalisms are based on DL-Lite logics with three types of concept inclusions (ranging…

Logic in Computer Science · Computer Science 2014-05-05 Alessandro Artale , Roman Kontchakov , Vladislav Ryzhikov , Michael Zakharyaschev

We study a category of probability spaces and measure-preserving Markov kernels up to almost sure equality. This category contains, among its isomorphisms, mod-zero isomorphisms of probability spaces. It also gives an isomorphism between…

Probability · Mathematics 2025-08-05 Noé Ensarguet , Paolo Perrone

Metric Temporal Logic (MTL) and Timed Propositional Temporal Logic (TPTL) extend Linear Temporal Logic (LTL) for real-time constraints, with MTL using time-bounded modalities and TPTL employing freeze quantifiers. Satisfiability for both is…

Logic in Computer Science · Computer Science 2024-11-04 Shankara Narayanan Krishna , Khushraj Madnani , Agnipratim Nag , Paritosh Pandya

The purpose of this paper is to develop further the main concepts of Phenomena Dynamic Logic (P-DL) and Cognitive Dynamic Logic (C-DL), presented in the previous paper. The specific character of these logics is in matching vagueness or…

Logic in Computer Science · Computer Science 2016-11-17 Evgenii Vityaev , Boris Kovalerchuk , Leonid Perlovsky , Stanislav Smerdov

By probabilistic logic I mean a normative theory of belief that explains how a body of evidence affects one's degree of belief in a possible hypothesis. A new axiomatization of such a theory is presented which avoids a finite additivity…

Artificial Intelligence · Computer Science 2013-04-10 Romas Aleliunas

Learning dynamics from dissipative chaotic systems is notoriously difficult due to their inherent instability, as formalized by their positive Lyapunov exponents, which exponentially amplify errors in the learned dynamics. However, many of…

Machine Learning · Computer Science 2024-06-07 Yair Schiff , Zhong Yi Wan , Jeffrey B. Parker , Stephan Hoyer , Volodymyr Kuleshov , Fei Sha , Leonardo Zepeda-Núñez

We extend the theory of labeled Markov processes with internal nondeterminism, a fundamental concept for the further development of a process theory with abstraction on nondeterministic continuous probabilistic systems. We define…

Logic in Computer Science · Computer Science 2015-03-17 Pedro D'Argenio , Pedro Sánchez Terraf , Nicolás Wolovick

Let L be some extension of classical propositional logic. The non-iterated probabilistic logic over L, is the logic PL that is defined by adding non-nested probabilistic operators in the language of L. For example in PL we can express a…

Logic in Computer Science · Computer Science 2019-02-12 Ioannis Kokkinis

Determining functionals are tools to describe the finite dimensional long-term dynamics of infinite dimensional dynamical systems. There also exist several applications to infinite dimensional {\em random} dynamical systems. In these…

Dynamical Systems · Mathematics 2016-08-16 Igor Chueshov , Jinqiao Duan , Björn Schmalfuß

We present limit theorems for a sequence of Piecewise Deterministic Markov Processes (PDMPs) taking values in a separable Hilbert space. This class of processes provides a rigorous framework for stochastic spatial models in which discrete…

Probability · Mathematics 2012-04-13 Martin G. Riedler , Michèle Thieullen , Gilles Wainrib

Dynamics and uncertainty are essential features of real-life argumentation, and many recent studies have focused on integrating both aspects into Dung's well-known abstract Argumentation Frameworks (AFs). This paper proposes a combination…

Logic in Computer Science · Computer Science 2023-02-08 Antonio Yuste-Ginel , Andreas Herzig

We introduce PHFL, a probabilistic extension of higher-order fixpoint logic, which can also be regarded as a higher-order extension of probabilistic temporal logics such as PCTL and the $\mu^p$-calculus. We show that PHFL is strictly more…

Logic in Computer Science · Computer Science 2023-06-22 Yo Mitani , Naoki Kobayashi , Takeshi Tsukada

A mathematical framework for Continuous Time Finance based on operator algebraic methods offers a new direct and entirely constructive perspective on the field and leads to new numerical analysis techniques. This is partly a review paper as…

Probability · Mathematics 2009-09-29 Claudio Albanese
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