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Unifying Refinement and Hoare-Style Reasoning in a logic for Higher-Order Concurrency

ACM SIGPLAN NOTICES 2013年第9期48卷 377-390页

作者： Turon, Aaron Dreyer, Derek Birkedal, Lars Aarhus Univ DK-8000 Aarhus C Denmark

Modular programming and modular verification go hand in hand, but most existing logics for concurrency ignore two crucial forms of modularity: higher-order functions, which are essential for building reusable components, and granularity abstraction, a key technique for hiding the intricacies of fine-grained concurrent data structures from the clients of those data structures. In this paper, we present CaReSL, the first logic to support the use of granularity abstraction for modular verification of higher-order concurrent programs. After motivating the features of CaReSL through a variety of illustrative examples, we demonstrate its effectiveness by using it to tackle a significant case study: the first formal proof of (partial) correctness for Hendler et al.'s "flat combining" algorithm.

关键词： Contextual refinement higher-order functions fine-grained concurrency separation logic Kripke logical relations

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Embed2Rule Scalable Neuro-Symbolic Learning via Latent Space Weak-Labelling 18th

Embed2Rule Scalable Neuro-Symbolic Learning via Latent Space...

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18th international conference on Neural-Symbolic Learning and Reasoning (NeSy)

作者： Aspis, Yaniv Albinhassan, Mohammad Lobo, Jorge Russo, Alessandra Imperial Coll London London England ICREA Barcelona Spain Univ Pompeu Fabra Barcelona Spain

ISBN: (纸本)9783031711664;9783031711671

Neuro-symbolic approaches have garnered much interest recently as a path toward endowing neural systems with robust reasoning capabilities. Most proposed end-to-end methods assume knowledge to be given in advance and do not scale up over many latent concepts. the recently proposed Embed2Sym tackles the scalability limitation by performing end-to-end neural training of a visual perception component from downstream labels to generate clusters in the latent space of symbolic concepts. these are later used to perform downstream symbolic reasoning but symbolic knowledge is still engineered. Taking inspiration from Embed2Sym, this paper introduces a novel method for scalable neuro-symbolic learning of first-order logic programs from raw data. the learned clusters are optimally labelled using sampled predictions of a pre-trained vision-language model. A SOTA symbolic learner, robust to noise, uses these labels to learn an answer set program that solves the reasoning task. Our approach, called Embed2Rule, is shown to achieve better accuracy than SOTA neuro-symbolic systems on existing benchmark tasks in most cases while scaling up to tasks that require far more complex reasoning and a large number of latent concepts.

关键词： Neuro-Symbolic AI Weak-Labelling Inductive logic programming

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Flexible exception handling in the OPERA process support system

Flexible exception handling in the OPERA process support sys...

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international conference on Distributed Computing Systems

作者： C. Hagen G. Alonso Information and Communication Systems Research Group Institute of Information Systems Swiss Federal Institute of Technology Zurich Switzerland

Exceptions are one of the most pervasive problems in process support systems. In installations expected to handle a large number of processes, having exceptions is bound to be a normal occurrence. Any programming tool intended for large, complex applications has to face this problem. However, current process support systems, despite their orientation towards complex, distributed, and heterogeneous applications, provide almost no support for exception handling. this paper shows how flexible mechanisms for failure handling are incorporated into the OPERA process support system using a combination of programming language concepts and transaction processing techniques. the resulting mechanisms allow the construction of fault-tolerant workflow processes in a transparent and flexible way while ensuring reusability of workflow components.

关键词： Computer languages Databases logic programming Humans Personnel Information systems Fault tolerant systems Environmental management logic design programming environments

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Induction of relational Fril rules

Induction of relational Fril rules

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conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： J.F. Baldwin C. Hill T.P. Martin Department of Engineering Mathematics University of Bristol Bristol UK

We propose an, approach to extend inductive logic programming (ILP) to cater for uncertainties in the form of probabilities and fuzzy sets. A corresponding decision tree induction algorithm that induces Fril (a support logic programming language) classification. Rules involving both forms of uncertainties is also described. this algorithm iteratively builds decision trees where each decision tree consists of one branch. this branch is directly translated into Fril rules that explain a part of the problem. the work presented focuses on propositional representations for both the input data values and the learned models. the approach is illustrated on the Pima Indian dataset. Finally an overview of the current work is given which deals with improving the algorithm with a new method for the calculation of support pairs and also with a new, user-independent stopping criterion for adding literals to the body of a rule.

关键词： Decision trees logic programming Uncertainty Iterative algorithms Fuzzy sets Classification tree analysis Partitioning algorithms Mathematics Fuzzy logic Entropy

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Reasoning on resident space object hierarchies using probabilistic programming

Reasoning on resident space object hierarchies using probabi...

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international conference on Information Fusion

作者： Brian E. Ruttenberg Matthew P. Wilkins Avi Pfeffer Charles River Analytics Cambridge MA Applied Defense Solutions Columbia MD

ISBN: (纸本)9781479974047

Hierarchical representations are common in many artificial intelligence tasks, such as classification of satellites in orbit. Representing and reasoning on hierarchies is difficult, however, as they can be large, deep and constantly evolving. Although probabilistic programming provides the flexibility to model many situations, current probabilistic programming languages (PPL) do not adequately support hierarchical reasoning. We present a novel PPL approach to representing and reasoning about hierarchies that utilizes references, enabling unambiguous access and referral to hierarchical objects and their properties. We demonstrate the benefits of our approach on a real-world resident space object hierarchy.

关键词： Low earth orbit satellites Probabilistic logic Cognition Space vehicles programming Orbits

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Leveraging Neurosymbolic AI for Slice Discovery 18th

Leveraging Neurosymbolic AI for Slice Discovery

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18th international conference on Neural-Symbolic Learning and Reasoning (NeSy)

作者： Collevati, Michele Eiter, thomas Higuera, Nelson Tech Univ Wien Inst Log & Computat Favoritenstr 9-11 A-1040 Vienna Austria

ISBN: (纸本)9783031711664;9783031711671

While remarkable recent developments in deep neural networks have significantly contributed to advancing the state-of-the-art in Computer Vision (CV), several studies have also shown their limitations and defects. In particular, CV models often make systematic errors on important subsets of data called slices, which are groups of data sharing a set of attributes. the slice discovery problem involves detecting semantically meaningful slices on which the model performs poorly, called rare slices. We propose a modular Neurosymbolic AI approach whose distinct advantage is the extraction of human-readable logical rules that describe rare slices, and thus enhances explainability of CV models. To this end, we present a methodology to induce rare slice occurrences in a model. Experiments on datasets from our data generator leveraging on Super-CLEVR show that the approach can correctly identify rare slices and produce logical rules describing them. the rules can be fruitfully used to generate new training data to mend model behavior or may be integrated into the model to enhance its inference capabilities. (the code for reproducing our experiments is available as an online repository: https://***/kbs/nesy- ai/ilp4sd).

关键词： Neurosymbolic AI Slice Discovery Inductive logic programming

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Distributed logic programming using mobile agents

Distributed logic programming using mobile agents

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international conference on Advanced Information Networking and Applications (AINA)

作者： T.I. Wang K.L. Clark Department of Engineering Science National Cheng Kung University Taiwan Department of Computing Imperial College London UK

We describe the use of mobile agent technologies in building a framework for supporting distributed logic programming and remote conditional querying. A mobile agent moves from server to server carrying its own knowledge. When it arrives at a server it is given read access to the some part of the server's knowledge base. It then answers its queries using the server's knowledge and its own, adding the results to its own knowledge. We can view the mobile agent's queries as conditional remote queries - what answers would the server give if the knowledge carried by the agent were added to the server. To implement a prototype framework of mobile agents and knowledge servers we have used a new multiparadigm and multi-threaded programming language Go !. this supports mobile agent's as knowledge objects and has powerful knowledge structuring features. We assume some familiarity with Prolog.

关键词： logic programming Mobile agents Prototypes Distributed computing Educational institutions Paper technology Computer languages Mobile communication Telecommunication traffic Computer applications

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Cable Length Minimisation in Long-Reach-PON Planning for Sparsely Populated Areas

Cable Length Minimisation in Long-Reach-PON Planning for Spa...

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18th international conference on Optical Network Design and Modeling (ONDM)

作者： Pal, Saptadeep Zukowski, Cezary Nag, Avishek Payne, David B. Ruffini, Marco Univ Dublin Trinity Coll CTVR Dublin 2 Ireland

ISBN: (纸本)9783901882609

Tackling the digital divide has become one of the main goals of many governments around the world, and a main target for the European Commission. Fibre-to-the-premises (FTTP) is the only access technology that has the potential to totally eliminate the digital divide since, within access distances, fibre capacity can be considered distance independent. In practice, however the higher cost means that many rural areas might not be served by FTTP services, further widening the capacity gap between rural and urban access. However, while fibre roll out is certainly less cost-effective in rural than urban areas, a proper deployment strategy that minimises cable installation costs can increase the network profitability and thus the rural FTTP coverage. In this paper, we propose a novel agglomerative clustering algorithm. the algorithm together with ILP and heuristic models, attempt to minimise the total fibre cable required to connect sparse rural users to a drop PON splitter located up to several kilometres away from the user. Our results show that proper deployment strategies can increase the use of large last-stage splitter, thus increasing sharing of fibre among users, while still minimising the overall cable length. In addition, we show that our heuristic is able to obtain similar results as the ILP (i.e. within an 8% margin), but can reduce the computation time by about 6 times, for the scenarios we have considered.

关键词： Clustering algorithms Joining processes Layout Minimization Passive optical networks Power cables Roads Clustering algorithms Passive optical networks Power cables layouts Road fiber-to-the-home inductive logic programming Rural Fiber cable computational time Consumers

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Pstable theories and Preferences

Pstable Theories and Preferences

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international conference on Electronics, Communications and Computers (CONIELECOMP)

作者： Mauricio Osorio Claudia Zepeda Universidad de las Américas-Puebla Mexico Benemérita Universidad Autónoma de Puebia Mexico

In this paper we introduce preference rules which allow us to specify preferences as an ordering among the possible solutions of a problem. Our approach allow us to express preferences for general theories and we defi... 详细信息

关键词： Intelligent agent logic programming Artificial intelligence US Department of Transportation Writing Proposals Computer science Processor scheduling Environmental economics Decision theory

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Granularity control for distributed execution of logic programs

Granularity control for distributed execution of logic progr...

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international conference on Distributed Computing Systems

作者： G. Xirogiannis Department of Computing & Electrical Engineering Heriot-Watt University UK

Distributed execution of logic programs requires a match of granularity between a program and the distributed multiprocessor it runs on to exploit its potential for performance fully. this paper presents methods to control the granularity of tasks on distributed heterogeneous processors effectively. It considers the characteristics of such platforms and relates the amount of local computation with the significant communication overheads by introducing the notion of a collection of parallel tasks. the experimental results indicate that the proposed controls can model all kinds of predicates (recursive, mutually recursive etc.) satisfactorily and improve the performance of various forms of parallelism (AND, OR, combinations).

关键词： Distributed control Parallel processing Communication system control Performance analysis Costs logic programming Engines Proposals Information analysis Automatic control

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