A First-Order Logic of Probability and Only Knowing in Unbounded Domains

Authors: Vaishak Belle, Gerhard Lakemeyer, Hector Levesque

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Reproducibility Variable Result LLM Response
Research Type Theoretical In this work, we propose a new general first-order account of probability and only knowing that admits knowledge bases with incomplete and probabilistic specifications. Beliefs and non-beliefs are then shown to emerge as a direct logical consequence of the sentences of the knowledge base at a corresponding level of specificity. We structure our work as follows. We begin by introducing the logic OBL (= OL+ degrees of belief modality). Then, we turn to properties and example specifications, OBL s relation to OL, discuss related work, and conclude.
Researcher Affiliation Academia Vaishak Belle Dept. of Computer Science KU Leuven Belgium vaishak@cs.kuleuven.be; Gerhard Lakemeyer Dept. of Computer Science RWTH Aachen University Germany gerhard@cs.rwth-aachen.de; Hector J. Levesque Dept. of Computer Science University of Toronto Canada hector@cs.toronto.edu. Supported by the Research Foundation-Flanders (FWOVlaanderen). Also affiliated with the University of Toronto.
Pseudocode No The paper defines a logical system with syntax, semantics, theorems, and proofs. It does not include any pseudocode or clearly labeled algorithm blocks.
Open Source Code No The paper does not mention or provide access to any open-source code for the described methodology. It is a theoretical paper focusing on formal logic.
Open Datasets No The paper is theoretical and focuses on developing a formal logic. It does not use or refer to any datasets for training or evaluation.
Dataset Splits No The paper is theoretical and does not involve empirical experiments with datasets, therefore it does not provide information about training, validation, or test splits.
Hardware Specification No The paper is theoretical and does not report on experiments that would require specific hardware. No hardware specifications are mentioned.
Software Dependencies No The paper is theoretical and focuses on formal logic; it does not describe experimental implementations that would require specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe an experimental setup, hyperparameters, or training configurations. It presents a logical framework and its properties.