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Humans and animals have the ability to reason and make predictions about different courses of action at many time scales. In reinforcement learning, option models (Sutton, Precup \& Singh, 1999; Precup, 2000) provide the framework for this…

Machine Learning · Computer Science 2021-08-09 Khimya Khetarpal , Zafarali Ahmed , Gheorghe Comanici , Doina Precup

Nonmonotonic logics are usually characterized by the presence of some notion of 'conditional' that fails monotonicity. Research on nonmonotonic logics is therefore largely concerned with the defeasibility of argument forms and the…

Logic in Computer Science · Computer Science 2013-10-29 Katarina Britz , Ivan Varzinczak

This paper is an original attempt to understand the foundations of economic reasoning. It endeavors to rigorously define the relationship between subjective interpretations and objective valuations of such interpretations in the context of…

Logic in Computer Science · Computer Science 2024-05-20 Daniel Lu

Transparency is an essential requirement of machine learning based decision making systems that are deployed in real world. Often, transparency of a given system is achieved by providing explanations of the behavior and predictions of the…

Machine Learning · Computer Science 2021-05-18 André Artelt , Barbara Hammer

To adequately model mathematical arguments the analyst must be able to represent the mathematical objects under discussion and the relationships between them, as well as inferences drawn about these objects and relationships as the…

Computation and Language · Computer Science 2018-07-17 Joseph Corneli , Ursula Martin , Dave Murray-Rust , Gabriela Rino Nesin , Alison Pease

The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules…

Artificial Intelligence · Computer Science 2007-05-23 Alejandro Javier Garcia , Guillermo Ricardo Simari

We introduce a formal operational semantics that describes the fused execution of variable contraction problems, which compute indexed arithmetic over a semiring and generalize sparse and dense tensor algebra, relational algebra, and graph…

Programming Languages · Computer Science 2022-07-28 Scott Kovach , Fredrik Kjolstad

Dung's abstract argumentation theory is a widely used formalism to model conflicting information and to draw conclusions in such situations. Hereby, the knowledge is represented by so-called argumentation frameworks (AFs) and the reasoning…

Artificial Intelligence · Computer Science 2016-04-01 Ringo Baumann , Thomas Linsbichler , Stefan Woltran

In order to study the problems of extending an action along a quotient of the acted object and along a quotient of the acting object, we investigate some properties of the fibration of points. In fact, we obtain a characterization of…

Category Theory · Mathematics 2016-03-29 Giuseppe Metere

We define a fragment of monadic infinitary second-order logic corresponding to an abstract separation property. We use this to define the concept of a separation subclass. We use model theoretic techniques and games to show that separation…

Logic · Mathematics 2021-12-09 Rob Egrot

Realizability for knowledge representation formalisms studies the following question: given a semantics and a set of interpretations, is there a knowledge base whose semantics coincides exactly with the given interpretation set? We…

Artificial Intelligence · Computer Science 2016-04-01 Thomas Linsbichler , Jörg Pührer , Hannes Strass

We consider dynamic versions of epistemic logic as formulated in Baltag and Moss "Logics for epistemic programs" (2004). That paper proposed a logical language (actually families of languages parameterized by action signatures) for dynamic…

Logic in Computer Science · Computer Science 2022-03-15 Alexandru Baltag , Lawrence S. Moss , Slawomir Solecki

Reasoning about the causes behind observations is crucial to the formalization of rationality. While extensive research has been conducted on root cause analysis, most studies have predominantly focused on deterministic settings. In this…

Artificial Intelligence · Computer Science 2024-12-24 Shakil M. Khan , Yves Lespérance , Maryam Rostamigiv

Explainable Artificial Intelligence and Formal Argumentation have received significant attention in recent years. Argumentation-based systems often lack explainability while supporting decision-making processes. Counterfactual and…

Artificial Intelligence · Computer Science 2024-05-08 Gianvincenzo Alfano , Sergio Greco , Francesco Parisi , Irina Trubitsyna

Structured prediction is ubiquitous in applications of machine learning such as knowledge extraction and natural language processing. Structure often can be formulated in terms of logical constraints. We consider the question of how to…

Artificial Intelligence · Computer Science 2017-09-27 Emmanouil Antonios Platanios , Ashish Kapoor , Eric Horvitz

Drawing appropriate defeasible inferences has been proven to be one of the most pervasive puzzles of natural language processing and a recurrent problem in pragmatics. This paper provides a theoretical framework, called ``stratified…

cmp-lg · Computer Science 2008-02-03 Daniel Marcu , Graeme Hirst

We consider multi-agent argumentation, where each agent's view of the arguments is encoded as an argumentation framework (AF). Then we study deliberative processes than can occur on this basis. We think of a deliberative process as taking…

Logic in Computer Science · Computer Science 2014-08-08 Truls Pedersen , Sjur Dyrkolbotn

We propose an approach based on Answer Set Programming for reasoning about actions with domain descriptions including ontological knowledge, expressed in the lightweight description logic EL^\bot. We consider a temporal action theory, which…

Artificial Intelligence · Computer Science 2021-07-20 Laura Giordano , Alberto Martelli , Daniele Theseider Dupré

Due to their inherent complexity, reasoning tasks have long been regarded as rigorous benchmarks for assessing the capabilities of machine learning models, especially large language models (LLMs). Although humans can solve these tasks with…

Artificial Intelligence · Computer Science 2026-03-30 Yunlong Deng , Boyang Sun , Yan Li , Lingjing Kong , Zeyu Tang , Kun Zhang , Guangyi Chen

We study first-order logic (FO) over the structure consisting of finite words over some alphabet $A$, together with the (non-contiguous) subword ordering. In terms of decidability of quantifier alternation fragments, this logic is…

Logic in Computer Science · Computer Science 2024-02-14 Pascal Baumann , Moses Ganardi , Ramanathan S. Thinniyam , Georg Zetzsche
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