Towards Closed World Reasoning in Dynamic Open Worlds (Extended Version)
Universidade Nova de Lisboa（新里斯本大学）
Martin Slota, João Leite
备注：
40 pages; an extended version of the article published in Theory and Practice of Logic Programming, 10 (4-6): 547 - 564, July. Copyright 2010 Cambridge University Press
发表信息：
Theory and Practice of Logic Programming, 10(4-6), 547-564, 2010
The need for integration of ontologies with nonmonotonic rules has been gaining importance in a number of areas, such as the Semantic Web. A number of researchers addressed this problem by proposing a unified semantics for hybrid knowledge bases composed of both an ontology (expressed in a fragment of first-order logic) and nonmonotonic rules. These semantics have matured over the years, but only provide solutions for the static case when knowledge does not need to evolve. In this paper we take a first step towards addressing the dynamics of hybrid knowledge bases. We focus on knowledge updates and, considering the state of the art of belief update, ontology update and rule update, we show that current solutions are only partial and difficult to combine. Then we extend the existing work on ABox updates with rules, provide a semantics for such evolving hybrid knowledge bases and study its basic properties. To the best of our knowledge, this is the first time that an update operator is proposed for hybrid knowledge bases.
Indian Statistical Institute（印度统计研究所）；Jadavpur University（贾达普大学）
Bilattice-based triangle provides an elegant algebraic structure for reasoning with vague and uncertain information. But the truth and knowledge ordering of intervals in bilattice-based triangle can not handle repetitive belief revisions which is an essential characteristic of nonmonotonic reasoning. Moreover the ordering induced over the intervals by the bilattice-based triangle is not sometimes intuitive. In this work, we construct an alternative algebraic structure, namely preorder-based triangle and we formulate proper logical connectives for this. It is also demonstrated that Preorder-bas…
University of the Basque Country (UPV/EHU)（巴斯克地区大学）
Most commonly, the Open World Assumption is adopted as a standard strategy for the design, construction and use of ontologies. This strategy limits the inferencing capabilities of any system because non-asserted statements (missing knowledge) could be assumed to be alternatively true or false. As we will demonstrate, this is especially the case of first-order logic (FOL) ontologies where non-asserted statements is nowadays one of the main obstacles to its practical application in automated commonsense reasoning tasks. In this paper, we investigate the application of the Closed World Assumption…
CLARK: Closed-loop Learning for Adaptive Reasoning over Knowledge Graphs
Sano - Centre for Computational Personalised Medicine（萨诺计算个性化医学中心）；CISUC/LASI, Department of Informatics Engineering, University of Coimbra（科英布拉大学信息工程系CISUC/LASI）；DeMaCS, University of Calabria（卡拉布里亚大学DeMaCS）
Free University of Bozen-Bolzano（博尔扎诺-博岑自由大学）；University of Osnabrück（奥斯纳布吕克大学）
We present a probabilistic extension of the description logic $\mathcal{ALC}$ for reasoning about statistical knowledge. We consider conditional statements over proportions of the domain and are interested in the probabilistic-logical consequences of these proportions. After introducing some general reasoning problems and analyzing their properties, we present first algorithms and complexity results for reasoning in some fragments of Statistical $\mathcal{ALC}$.
Free University of Bozen-Bolzano（博尔扎诺自由大学）；University of Osnabrück（奥斯纳布吕克大学）
A central question for knowledge representation is how to encode and handle uncertain knowledge adequately. We introduce the probabilistic description logic ALCP that is designed for representing context-dependent knowledge, where the actual context taking place is uncertain. ALCP allows the expression of logical dependencies on the domain and probabilistic dependencies on the possible contexts. In order to draw probabilistic conclusions, we employ the principle of maximum entropy. We provide reasoning algorithms for this logic, and show that it satisfies several desirable properties of probab…
The recent Control Argumentation Framework (CAF) is a generalization of Dung's Argumentation Framework which handles argumentation dynamics under uncertainty; especially it can be used to model the behavior of an agent which can anticipate future changes in the environment. Here we provide new insights on this model by defining the notion of possible controllability of a CAF. We study the complexity of this new form of reasoning for the four classical semantics, and we provide a logical encoding for reasoning with this framework.
FZI Research Center for Information Technology（FZI信息技术研究中心）；University of Miami（迈阿密大学）
OWL 2 has been standardized by the World Wide Web Consortium (W3C) as a family of ontology languages for the Semantic Web. The most expressive of these languages is OWL 2 Full, but to date no reasoner has been implemented for this language. Consistency and entailment checking are known to be undecidable for OWL 2 Full. We have translated a large fragment of the OWL 2 Full semantics into first-order logic, and used automated theorem proving systems to do reasoning based on this theory. The results are promising, and indicate that this approach can be applied in practice for effective OWL reason…
Deontic logic is shown to be applicable for modelling human reasoning. For this the Wason selection task and the suppression task are discussed in detail. Different versions of modelling norms with deontic logic are introduced and in the case of the Wason selection task it is demonstrated how differences in the performance of humans in the abstract and in the social contract case can be explained. Furthermore it is shown that an automated theorem prover can be used as a reasoning tool for deontic logic.
University of Innsbruck（因斯布鲁克大学）；Radboud University Nijmegen（拉德堡德大学奈梅亨分校）
Machine Learner for Automated Reasoning (MaLARea) is a learning and reasoning system for proving in large formal libraries where thousands of theorems are available when attacking a new conjecture, and a large number of related problems and proofs can be used to learn specific theorem-proving knowledge. The last version of the system has by a large margin won the 2013 CASC LTB competition. This paper describes the motivation behind the methods used in MaLARea, discusses the general approach and the issues arising in evaluation of such system, and describes the Mizar@Turing100 and CASC'24 versi…
Indian Statistical Institute（印度统计研究所）；Jadavpur University（贾达夫普尔大学）
An interval-valued fuzzy answer set programming paradigm is proposed for nonmonotonic reasoning with vague and uncertain information. The set of sub-intervals of $[0,1]$ is considered as truth-space. The intervals are ordered using preorder-based truth and knowledge ordering. The preorder based ordering is an enhanced version of bilattice-based ordering. The system can represent and reason with prioritized rules, rules with exceptions. An iterative method for answer set computation is proposed. The sufficient conditions for termination of iterations are identified for a class of logic programs…
Complexity in finitary argumentation (extended version)
Department of Mathematics, University of Wisconsin-Madison（威斯康星大学麦迪逊分校数学系）；Department of Humanistic Research and Innovation, University of Bari（巴里大学人文研究与创新系）
Description logics are a powerful tool for describing ontological knowledge bases. That is, they give a factual account of the world in terms of individuals, concepts and relations. In the presence of uncertainty, such factual accounts are not feasible, and a subjective or epistemic approach is required. Aleatoric description logic models uncertainty in the world as aleatoric events, by the roll of the dice, where an agent has subjective beliefs about the bias of these dice. This provides a subjective Bayesian description logic, where propositions and relations are assigned probabilities accor…
The paper investigates the relative expressiveness of two logic-based languages for reasoning over streams, namely LARS Programs -- the language of the Logic-based framework for Analytic Reasoning over Streams called LARS -- and LDSR -- the language of the recent extension of the I-DLV system for stream reasoning called I-DLV-sr. Although these two languages build over Datalog, they do differ both in syntax and semantics. To reconcile their expressive capabilities for stream reasoning, we define a comparison framework that allows us to show that, without any restrictions, the two languages are…
University of Greifswald（格赖夫斯瓦尔德大学）；University of Luxembourg（卢森堡大学）；University of Bamberg（班贝格大学）
LegalRuleML is a comprehensive XML-based representation framework for modeling and exchanging normative rules. The TPTP input and output formats, on the other hand, are general-purpose standards for the interaction with automated reasoning systems. In this paper we provide a bridge between the two communities by (i) defining a logic-pluralistic normative reasoning language based on the TPTP format, (ii) providing a translation scheme between relevant fragments of LegalRuleML and this language, and (iii) proposing a flexible architecture for automated normative reasoning based on this translati…
University of Edinburgh（爱丁堡大学）；University of Oxford（牛津大学）
Compact closed categories provide a foundational formalism for a variety of important domains, including quantum computation. These categories have a natural visualisation as a form of graphs. We present a formalism for equational reasoning about such graphs and develop this into a generic proof system with a fixed logical kernel for equational reasoning about compact closed categories. Automating this reasoning process is motivated by the slow and error prone nature of manual graph manipulation. A salient feature of our system is that it provides a formal and declarative account of derived re…
When Do LLMs Apply the Wrong Law? Diagnosing LLM Failures in Temporal Legal Reasoning
Institute of Science Tokyo（东京科学大学）；Osaka University（大阪大学）；NII LLMC（日本信息学研究所语言、语言学与媒体中心）；Nara Institute of Science and Technology（奈良科学技术研究所）；Center of Juris-Informatics, ROIS-DS（日本学术研究推进机构跨学科科学研究中心法学信息学中心）
Faithful or Just Plausible? Evaluating the Faithfulness of Closed-Source LLMs in Medical Reasoning
Stratified Precision；Harvard Medical School（哈佛医学院）；Imperial College London（帝国理工学院伦敦分校）；National Health Service（国家健康服务系统）；Ipsen France（Ipsen法国）；University College London（伦敦大学学院）
Heterogeneous Element-Aware Cross-Version Differencing of Scientific Documents via Layout-Aware Alignment and Structure-Aware Reasoning
Beijing Renhe Information Technology Co., Ltd.（北京人和信息技术有限公司）；Key Laboratory of Digital Publishing and Total Process Management of Scientific and Technical Journals（科技期刊数字出版与全程管理重点实验室）
Most work on physical reasoning, both in artificial intelligence and in cognitive science, has focused on closed-world reasoning, in which it is assumed that the problem specification specifies all relevant objects and substance, all their relations in an initial situation, and all exogenous events. However, in many situations, it is important to do open-world reasoning; that is, making valid conclusions from very incomplete information. We have implemented in Prolog an open-world reasoner for a toy microworld of containers that can be loaded, unloaded, sealed, unsealed, carried, and dumped.
ReasonPlan: Unified Scene Prediction and Decision Reasoning for Closed-loop Autonomous Driving
SKL-MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China（中国科学院自动化研究所SKL-MAIS部门，北京）；School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China（中国科学院大学人工智能学院，北京）；EACON, Fujian, China（福建EACON机构，中国）；School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China（北京科技大学自动化与电气工程学院）
Compact closed categories have found applications in modeling quantum information protocols by Abramsky-Coecke. They also provide semantics for Lambek's pregroup algebras, applied to formalizing the grammatical structure of natural language, and are implicit in a distributional model of word meaning based on vector spaces. Specifically, in previous work Coecke-Clark-Sadrzadeh used the product category of pregroups with vector spaces and provided a distributional model of meaning for sentences. We recast this theory in terms of strongly monoidal functors and advance it via Frobenius algebras ov…
The goal of neural-symbolic computation is to integrate the connectionist and symbolist paradigms. Prior methods learn the neural-symbolic models using reinforcement learning (RL) approaches, which ignore the error propagation in the symbolic reasoning module and thus converge slowly with sparse rewards. In this paper, we address these issues and close the loop of neural-symbolic learning by (1) introducing the \textbf{grammar} model as a \textit{symbolic prior} to bridge neural perception and symbolic reasoning, and (2) proposing a novel \textbf{back-search} algorithm which mimics the top-dow…
The formalizations of periods of time inside a linear model of Time are usually based on the notion of intervals, that may contain or may not their endpoints. This is not enought when the periods are written in terms of coarse granularities with respect to the event taken into account. For instance, how to express the inter-war period in terms of a {\em years} interval? This paper presents a new type of intervals, neither open, nor closed or open-closed and the extension of operations on intervals of this new type, in order to reduce the gap between the discourse related to temporal relationsh…
Prior work in standardized science exams requires support from large text corpus, such as targeted science corpus fromWikipedia or SimpleWikipedia. However, retrieving knowledge from the large corpus is time-consuming and questions embedded in complex semantic representation may interfere with retrieval. Inspired by the dual process theory in cognitive science, we propose a MetaQA framework, where system 1 is an intuitive meta-classifier and system 2 is a reasoning module. Specifically, our method based on meta-learning method and large language model BERT, which can efficiently solve science …
B. Verkin Institute for Low Temperature Physics and Engineering of the National Academy of Sciences of Ukraine（乌克兰国家科学院B·维尔金低温物理与工程研究所）
Based on ideas of quantum theory of open systems and psychological dual system theory we propose two novel versions of Non-Boolean logic. The first version can be interpreted in our opinion as simplified description of primitive (mythological) thinking and the second one as the toy model of everyday human reasoning in which aside from logical deduction, heuristic elements and beliefs also play the considerable role. Several arguments in favor of the interpretations proposed are adduced and discussed in the paper as well.
Multi-Agent Closed-Loop Reasoning for Organic Structure Elucidation from Multimodal Spectra
Shanghai Jiao Tong University（上海交通大学）；Institute of Process Engineering, Chinese Academy of Sciences（中国科学院过程工程研究所）；Huashan Hospital, Fudan University（复旦大学附属华山医院）；Minhang District Center for Disease Control（闵行区疾病预防控制中心）；Johns Hopkins University（约翰斯·霍普金斯大学）；National Clinical Research Center for Kidney Diseases（国家肾脏疾病临床医学研究中心）
Computer Science and Communications, University of Luxembourg（卢森堡大学计算机科学与通信学院）
A flexible infrastructure for normative reasoning is outlined. A small-scale demonstrator version of the envisioned system has been implemented in the proof assistant Isabelle/HOL by utilising the first authors universal logical reasoning approach based on shallow semantical embeddings in meta-logic HOL. The need for such a flexible reasoning infrastructure is motivated and illustrated with a contrary-to-duty example scenario selected from the General Data Protection Regulation.
This paper is mainly concerned with the relation-algebraical aspects of the well-known Region Connection Calculus (RCC). We show that the contact relation algebra (CRA) of certain RCC model is not atomic complete and hence infinite. So in general an extensional composition table for the RCC cannot be obtained by simply refining the RCC8 relations. After having shown that each RCC model is a consistent model of the RCC11 CT, we give an exhaustive investigation about extensional interpretation of the RCC11 CT. More important, we show the complemented closed disk algebra is a representation for t…
EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis
School of Biological Science and Medical Engineering, Southeast University（东南大学生物科学与医学工程学院）；Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University（江苏省生物材料与器件重点实验室）；State Key Laboratory of Digital Medical Engineering, Southeast University（国家数字医学工程重点实验室）；The First Affiliated Hospital of Nanjing Medical University（南京医科大学第一附属医院）；Department of Computer Science and Engineering, The Chinese University of Hong Kong（香港中文大学计算机科学与工程系）；Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing（江苏省联合国际医学信息处理联合实验室）；Laboratory of Image Science and Technology, the School of Computer Science and Engineering, Southeast University（图像科学与技术实验室，东南大学计算机科学与工程学院）
LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios
Institute for AI Industry Research (AIR), Tsinghua University（清华大学人工智能产业研究院（AIR））；Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术系）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Horizon Robotics（地平线机器人）
Freie Universität Berlin（柏林自由大学）；University of Potsdam（波茨坦大学）
A converter from first-order modal logics to classical higher- order logic is presented. This tool enables the application of off-the-shelf higher-order theorem provers and model finders for reasoning within first- order modal logics. The tool supports logics K, K4, D, D4, T, S4, and S5 with respect to constant, varying and cumulative domain semantics.
MIT CSAIL（麻省理工学院计算机科学与人工智能实验室）；Harvard SEAS（哈佛大学约翰·A·保尔森工程与应用科学学院）
We consider the problem of answering queries about formulas of propositional logic based on background knowledge partially represented explicitly as other formulas, and partially represented as partially obscured examples independently drawn from a fixed probability distribution, where the queries are answered with respect to a weaker semantics than usual -- PAC-Semantics, introduced by Valiant (2000) -- that is defined using the distribution of examples. We describe a fairly general, efficient reduction to limited versions of the decision problem for a proof system (e.g., bounded space treeli…
