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This paper introduces a new approach for continual planning and model learning in relational, non-stationary stochastic environments. Such capabilities are essential for the deployment of sequential decision-making systems in the uncertain…

Artificial Intelligence · Computer Science 2024-07-24 Rushang Karia , Pulkit Verma , Alberto Speranzon , Siddharth Srivastava

Recent technological advances have led to unprecedented amounts of generated data that originate from the Web, sensor networks and social media. Analytics in terms of defeasible reasoning - for example for decision making - could provide…

Logic in Computer Science · Computer Science 2021-02-16 Michael J. Maher , Ilias Tachmazidis , Grigoris Antoniou , Stephen Wade , Long Cheng

Recent developments in aligning Large Language Models (LLMs) with human preferences have significantly enhanced their utility in human-AI collaborative scenarios. However, such approaches often neglect the critical role of "epistemic…

Computation and Language · Computer Science 2025-06-13 Timothy Obiso , Kenneth Lai , Abhijnan Nath , Nikhil Krishnaswamy , James Pustejovsky

Categorization systems are widely studied in psychology, sociology, and organization theory as information-structuring devices which are critical to decision-making processes. In the present paper, we introduce a sound and complete…

Logic in Computer Science · Computer Science 2017-07-28 Willem Conradie , Sabine Frittella , Alessandra Palmigiano , Michele Piazzai , Apostolos Tzimoulis , Nachoem M. Wijnberg

The interpretation of propositional dynamic logic (PDL) through Kripke models requires the relations constituting the interpreting Kripke model to closely observe the syntax of the modal operators. This poses a significant challenge for an…

Logic in Computer Science · Computer Science 2011-09-19 Ernst-Erich Doberkat

Applying automated reasoning tools for decision support and analysis in law has the potential to make court decisions more transparent and objective. Since there is often uncertainty about the accuracy and relevance of evidence,…

Artificial Intelligence · Computer Science 2020-09-15 Inga Ibs , Nico Potyka

Dynamic scheduling is an important problem in applications from queuing to wireless networks. It addresses how to choose an item among multiple scheduling items in each timestep to achieve a long-term goal. Conventional approaches for…

Machine Learning · Computer Science 2022-01-26 Hyun-Suk Lee

Epistemic graphs are a generalization of the epistemic approach to probabilistic argumentation. Hunter proposed a 2-way generalization framework to learn epistemic constraints from crowd-sourcing data. However, the learnt epistemic…

Artificial Intelligence · Computer Science 2023-06-08 Xiao Chi

A delayed term in a differential equation reflects the fact that information takes significant time to travel from one place to another within a process being studied. Despite de apparent similarity with ordinary differential equations,…

Dynamical Systems · Mathematics 2023-08-24 Gregory Kozyreff

In this survey we review dynamic epistemic logics with modalities for quantification over information change. Of such logics we present complete axiomatizations, focussing on axioms involving the interaction between knowledge and such…

Logic in Computer Science · Computer Science 2023-03-22 Hans van Ditmarsch

Epistemic Logic Programs (ELPs) extend Answer Set Programming (ASP) with epistemic negation and have received renewed interest in recent years. This led to the development of new research and efficient solving systems for ELPs. In practice,…

Logic in Computer Science · Computer Science 2020-02-19 Wolfgang Faber , Michael Morak , Stefan Woltran

Modeling of complex phenomena such as the mind presents tremendous computational complexity challenges. Modeling field theory (MFT) addresses these challenges in a non-traditional way. The main idea behind MFT is to match levels of…

Logic · Mathematics 2010-12-27 Boris Kovalerchuk , Leonid Perlovsky , Gregory Wheeler

The logics of knowledge are modal logics that have been shown to be effective in representing and reasoning about knowledge in multi-agent domains. Relatively few computational frameworks for dealing with computation of models and useful…

Artificial Intelligence · Computer Science 2010-07-22 Chitta Baral , Gregory Gelfond , Enrico Pontelli , Tran Cao Son

Answer Set Programming (ASP) is a prominent problem-modeling and solving framework, whose solutions are called answer sets. Epistemic logic programs (ELP) extend ASP to reason about all or some answer sets. Solutions to an ELP can be seen…

Logic in Computer Science · Computer Science 2025-03-10 Thomas Eiter , Johannes K. Fichte , Markus Hecher , Stefan Woltran

Collective Adaptive Systems often consist of many heterogeneous components typically organised in groups. These entities interact with each other by adapting their behaviour to pursue individual or collective goals. In these systems, the…

Logic in Computer Science · Computer Science 2024-02-14 Michele Loreti , Michela Quadrini

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

We propose a novel deep network architecture for lifelong learning which we refer to as Dynamically Expandable Network (DEN), that can dynamically decide its network capacity as it trains on a sequence of tasks, to learn a compact…

Machine Learning · Computer Science 2018-06-12 Jaehong Yoon , Eunho Yang , Jeongtae Lee , Sung Ju Hwang

The tractability of the lightweight description logic EL has allowed for the construction of large and widely used ontologies that support semantic interoperability. However, comprehensive domains with a broad user base are often at odds…

Artificial Intelligence · Computer Science 2023-05-11 Lucía Gómez Álvarez , Sebastian Rudolph , Hannes Strass

We present a novel framework designed to extend model reconciliation approaches, commonly used in human-aware planning, for enhanced human-AI interaction. By adopting a structured argumentation-based dialogue paradigm, our framework enables…

Artificial Intelligence · Computer Science 2024-08-09 Stylianos Loukas Vasileiou , Ashwin Kumar , William Yeoh , Tran Cao Son , Francesca Toni

Epistemic reasoning requires agents to infer the state of the world from partial observations and information about other agents' knowledge. Prior work evaluating LLMs on canonical epistemic puzzles interpreted their behavior through a…

Computation and Language · Computer Science 2026-03-24 Adi Gabay , Gabriel Stanovsky , Liat Peterfreund