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17th international conference on Principles of Knowledge Representation and reasoning (KR and R)

作者： Penaloza, Rafael Univ Milano Bicocca Milan Italy

ISBN: (纸本)9780999241172

We currently have access to a plethora of statistical analyses based on sampling limited parts of a population. Meta-analysis is the task of combining several statistical results to obtain a more precise and reliable picture of the population. By the nature of sampling, all these results are uncertain, and difficult to combine with other knowledge. In this position paper, we propose a first approach for automated reasoning in meta-analyses.

关键词： Sampling

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A First-Order logic of Limited Belief Based on Possible Worlds 17

A First-Order Logic of Limited Belief Based on Possible Worl...

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17th international conference on Principles of Knowledge Representation and reasoning (KR and R)

作者： Lakemeyer, Gerhard Levesque, Hector J. Rhein Westfal TH Aachen Dept Comp Sci Aachen Germany Univ Toronto Dept Comp Sci Toronto ON Canada

ISBN: (纸本)9780999241172

In a recent paper Lakemeyer and Levesque proposed a first-order logic of limited belief to characterize the beliefs of a knowledge base (KB). Among other things, they show that their model of belief is expressive, eventually complete, and tractable. this means, roughly, that a KB may consist of arbitrary first-order sentences, that any sentence which is logically entailed by the KB is eventually believed, given enough reasoning effort, and that reasoning is tractable under reasonable assumptions. One downside of the proposal is that epistemic states are defined in terms of sets of clauses, possibly containing variables, giving the logic a distinct syntactic flavour compared to the more traditional possible-world semantics found in the literature on epistemic logic. In this paper we show that the same properties as above can be obtained by defining epistemic states as sets of three-valued possible worlds. this way we are able to shed new light on those properties by recasting them using the more familiar notion of truth over possible worlds.

关键词： Semantics

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Modelling Multi-Agent Epistemic Planning in ASP

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thEORY AND PRACTICE OF logic programming 2020年第5期20卷 593-608页

作者： Burigana, Alessandro Fabiano, Francesco Dovier, Agostino Pontelli, Enrico Univ Udine Udine Italy New Mexico State Univ Las Cruces NM 88003 USA

Designing agents that reason and act upon the world has always been one of the main objectives of the artificial intelligence community. While for planning in "simple" domains the agents can solely rely on facts about the world, in several contexts,e.g., economy, security, justice and politics, the mere knowledge of the world could be insufficient to reach a desired goal. In these scenarios,epistemicreasoning,i.e., reasoning about agents' beliefs about themselves and about other agents' beliefs, is essential to design winning strategies. this paper addresses the problem of reasoning in multi-agent epistemic settings exploiting declarative programming techniques. In particular, the paper presents an actual implementation of a multi-shotAnswer Set programming-based planner that can reason in multi-agent epistemic settings, called PLATO (ePistemic muLti-agentAnswer seTprogramming sOlver). the ASP paradigm enables a concise and elegant design of the planner, w.r.t. other imperative implementations, facilitating the development of formal verification of correctness. the paper shows how the planner, exploiting an ad-hoc epistemic state representation and the efficiency of ASP solvers, has competitive performance results on benchmarks collected from the literature.

关键词： Epistemic reasoning Multi-Shot ASP Planning Multi-Agent Possibilities

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An Entropic Approach to Technology Enable Learning and Social Computing 4

An Entropic Approach to Technology Enable Learning and Socia...

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4th international conference on Machine Learning and Intelligent Systems, MLIS 2022

作者： Alves, Victor Miranda, José Dawa, Hossam Fernandes, Filipe Pombal, Fernanda Ribeiro, Jorge Fdez-Riverola, Florentino Analide, Cesar Vicente, Henrique Neves, José ADiT-LAB Instituto Politécnico de Viana Do Castelo Viana do Castelo Portugal Cinbio Universidade de Vigo Department of Computer Science ESEI-Escuela Superior de Ingeniería Informática Ourense32004 Spain Sing Research Group Galicia sur Health Research Institute SERGAS-UVIGO Spain Instituto Politécnico de Saúde Do Norte Cespu Famalicão Portugal Universidade Católica Portuguesa Instituto de Ciências da Saúde Porto Portugal Algoritmi Research Centre/LASI University of Minho Braga Portugal Departamento de Química e Bioquímica Escola de Ciências e Tecnologia REQUIMTE/LAQV Universidade de Évora Évora Portugal

ISBN: (纸本)9781643683560

Understanding one's own behavior is challenging in itself;understanding a group of different individuals and the many relationships between these individuals is even more complex. Imagine the amazing complexity of a large system made up of thousands of individuals and hundreds of groups, with countless relationships between those individuals and groups. However, despite this difficulty, organizations must be managed. Indeed, ultimately the organization's work is done by people, individually or collectively, alone or in combination with technology. therefore, organizational behavior management is the central task of management work-it involves understanding the behavior patterns of individuals, groups, and organizations, predicting what behavioral reactions will be elicited by various managerial actions and finally applying this understanding. Undeniably, society's work is often done by organizations, and the role of management is to make organizations do that work. Without it, our entire society would quickly stop operating. Not only would the products you have come to know and love swiftly to evaporate from store shelves;food itself would suddenly become scarce, having drastic effects on huge numbers of people. To this end, the term Technology-Enhanced Learning is used to support workers' learning about technology;the gap between what is understood to be satisfactory and the current level of knowledge of the workforce is addressed by a logic-programming-based Social Computing Framework entitled An Entropic Approach to Knowledge Representation and reasoning, which relies on computational structures built on artificial Neural Networks and Cases-based thinking, as well as predictions and/or assessments, to empower the level of knowledge of the employees, here in technology, later in other areas. © 2022 the authors and IOS Press.

关键词： Case based reasoning

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WOLED: A Tool for Online Learning Weighted Answer Set Rules for Temporal reasoning Under Uncertainty 17

WOLED: A Tool for Online Learning Weighted Answer Set Rules ...

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17th international conference on Principles of Knowledge Representation and reasoning (KR and R)

作者： Katzouris, Nikos Artikis, Alexander Natl Ctr Sci Res Demokritos Athens Greece Univ Pireaus Piraeus Greece

ISBN: (纸本)9780999241172

Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event pattern authoring. We presentWOLED, a system based on Answer Set programming (ASP), capable of probabilistic reasoning with complex event patterns in the form of weighted rules in the Event Calculus, whose structure and weights are learnt online. We compare our ASP-based implementation with a Markov logic-based one and with a crisp version of the algorithm that learns unweighted rules, on CER datasets for activity recognition, maritime surveillance and fleet management. Our results demonstrate the superiority of our novel implementation, both in terms of efficiency and predictive performance.

关键词： Calculations

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Combining Deep Learning and ASP-Based Models for the Semantic Segmentation of Medical Images 5th

Combining Deep Learning and ASP-Based Models for the Semanti...

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5th international Joint conference on Rules and reasoning (RuleML+RR)

作者： Bruno, Pierangela Calimeri, Francesco Marte, Cinzia Manna, Marco Univ Calabria Dept Math & Comp Sci Arcavacata Di Rende Italy

ISBN: (纸本)9783030911676;9783030911669

Automatic segmentation represents a huge breakthrough in computer-aided diagnosis and medicine, as it allows to provide clinicians important with information for interventional and diagnostic tasks. Recent advancements in Deep Learning (DL), such as Convolutional Neural Networks (CNNs), have proved to be greatly promising in identifying anatomical and pathological structures, and in extracting meaningful patterns from huge amounts of data. However, such approaches suffer from the lack of proper means for interpreting the choices made by the models, and it is not easy to drive the decisions according to prior knowledge. In this context, deductive rule-based approaches, such as Answer Set programming (ASP), can allow to effectively encode problems or specific features via logic programs in a declarative fashion, while possibly also helping at improving performance. In this seminal work, we propose the use of ASP to drive DL approaches in performing semantic segmentation of medical images. Specifically, we encoded prior medical knowledge via ASP, thus defining a rule-based model for deducting all admitted combinations of classes and right locations in medical images. the results of an experimental analysis are reported with the aim to assess the viability of the proposed approach.

关键词： Answer set programming Knowledge representation and reasoning Deep learning Semantic segmentation Inductive-deductive coupling

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Nondeterministic Strategies and their Refinement in Strategy logic 17

Nondeterministic Strategies and their Refinement in Strategy...

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17th international conference on Principles of Knowledge Representation and reasoning (KR and R)

作者： De Giacomo, Giuseppe Maubert, Bastien Murano, Aniello Sapienza Univ Roma Rome Italy Univ Napoli Federico II Naples Italy

ISBN: (纸本)9780999241172

Nondeterministic strategies are strategies (or protocols, or plans) that, given a history in a game, assign a set of possible actions, all of which should be winning. An important problem is that of refining such strategies. For instance, given a nondeterministic strategy that allows only safe executions, refine it to, additionally, eventually reach a desired state of affairs. We show that strategic problems involving strategy refinement can be solved elegantly in the framework of Strategy logic (SL), a very expressive logic to reason about strategic abilities. Specifically, we introduce an extension of SL with nondeterministic strategies and an operator expressing strategy refinement. We show that model checking this logic can be done at no additional computational cost with respect to standard SL, and can be used to solve a variety of problems such as synthesis of maximally permissive strategies or maximally permissive Nash equilibria.

关键词： Model checking

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Inputs, Outputs, and Composition in the logic of Information Flows 17

Inputs, Outputs, and Composition in the Logic of Information...

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17th international conference on Principles of Knowledge Representation and reasoning (KR and R)

作者： Aamer, Heba Bogaerts, Bart Surinx, Dimitri Ternovska, Eugenia Van den Bussche, Jan Univ Hasselt Hasselt Belgium Vrije Univ Brussel Brussels Belgium Simon Fraser Univ Burnaby BC Canada

ISBN: (纸本)9780999241172

the logic of information flows (LIF) is a general framework in which tasks of a procedural nature can be modeled in a declarative, logic-based fashion. the first contribution of this paper is to propose semantic and syntactic definitions of inputs and outputs of LIF expressions. We study how the two relate and show that our syntactic definition is optimal in a sense that is made precise. the second contribution is a systematic study of the expressive power of sequential composition in LIF. Our results on composition tie in the results on inputs and outputs, and relate LIF to first-order logic (FO) and bounded-variable LIF to bounded-variable FO.

关键词： Syntactics

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Concept Contraction in the Description logic EL 17

Concept Contraction in the Description Logic EL

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17th international conference on Principles of Knowledge Representation and reasoning (KR and R)

作者： Rienstra, Tjitze Schon, Claudia Staab, Steffen Univ Koblenz Landau Mainz Germany Univ Stuttgart Stuttgart Germany Univ Southampton Southampton Hants England

ISBN: (纸本)9780999241172

In this paper we study the problem of concept contraction for the description logic EL. Concept contraction is concerned with the following question: Given two concepts C and D (with the interesting case being that D subsumes C) how can we find a generalisation of C that is not subsumed by D but is otherwise as similar as possible to C? We take an AGM-style approach and model this problem using the notion of a concept contraction operator. We consider constructive definitions as well as sets of postulates for concept contraction, and link the two by means of representation theorems.

关键词： Data description

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reasoning with Contextual Knowledge and Influence Diagrams 17

Reasoning with Contextual Knowledge and Influence Diagrams

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17th international conference on Principles of Knowledge Representation and reasoning (KR and R)

作者： Acar, Erman Penaloza, Rafael Vrije Univ Amsterdam Amsterdam Netherlands Univ Milano Bicocca Milan Italy

ISBN: (纸本)9780999241172

Influence diagrams (IDs) are well-known formalisms extending Bayesian networks to model decision situations under uncertainty. Although they are convenient as a decision theoretic tool, their knowledge representation ability is limited in capturing other crucial notions such as logical consistency. We complement IDs with the light-weight description logic (DL) EL to overcome such limitations. We consider a setup where DL axioms hold in some contexts, yet the actual context is uncertain. the framework benefits from the convenience of using DL as a domain knowledge representation language and the modelling strength of IDs to deal with decisions over contexts in the presence of contextual uncertainty. We define related reasoning problems and study their computational complexity.

关键词： Knowledge representation

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