A Brief History of Updates of Answer-Set Programs

Funding Information: The authors would like to thank José Alferes, Martin Baláz, Federico Banti, Antonio Brogi, Martin Homola, Luís Moniz Pereira, Halina Przymusinska, Teodor C. Przymusinski, and Theresa Swift, with whom they worked on the topic of this paper over the years, as well as Ricardo Gonçalves and Matthias Knorr for valuable comments on an earlier draft of this paper. The authors would also like to thank the anonymous reviewers for their insightful comments and suggestions, which greatly helped us improve this paper. The authors were partially supported by Fundação para a Ciência e Tecnologia through projects FORGET (PTDC/CCI-INF/32219/2017) and RIVER (PTDC/CCI-COM/30952/2017), and strategic project NOVA LINCS (UIDB/04516/2020). Publisher Copyright: © The Author(s), 2022. Published by Cambridge University Press.Over the last couple of decades, there has been a considerable effort devoted to the problem of updating logic programs under the stable model semantics (a.k.a. answer-set programs) or, in other words, the problem of characterising the result of bringing up-to-date a logic program when the world it describes changes. Whereas the state-of-the-art approaches are guided by the same basic intuitions and aspirations as belief updates in the context of classical logic, they build upon fundamentally different principles and methods, which have prevented a unifying framework that could embrace both belief and rule updates. In this paper, we will overview some of the main approaches and results related to answer-set programming updates, while pointing out some of the main challenges that research in this topic has faced.publishersversionpublishe

Towards Closed World Reasoning in Dynamic Open Worlds (Extended Version)

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.Comment: 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 Pres

Magnetic edge states and coherent manipulation of graphene nanoribbons

Graphene, a single-layer network of carbon atoms, has outstanding electrical and mechanical properties. Graphene ribbons with nanometre-scale widths (nanoribbons) should exhibit half-metallicity and quantum confinement. Magnetic edges in graphene nanoribbons have been studied extensively from a theoretical standpoint because their coherent manipulation would be a milestone for spintronic and quantum computing devices. However, experimental investigations have been hampered because nanoribbon edges cannot be produced with atomic precision and the graphene terminations that have been proposed are chemically unstable. Here we address both of these problems, by using molecular graphene nanoribbons functionalized with stable spin-bearing radical groups. We observe the predicted delocalized magnetic edge states and test theoretical models of the spin dynamics and spin–environment interactions. Comparison with a non-graphitized reference material enables us to clearly identify the characteristic behaviour of the radical-functionalized graphene nanoribbons. We quantify the parameters of spin–orbit coupling, define the interaction patterns and determine the spin decoherence channels. Even without any optimization, the spin coherence time is in the range of microseconds at room temperature, and we perform quantum inversion operations between edge and radical spins. Our approach provides a way of testing the theory of magnetism in graphene nanoribbons experimentally. The coherence times that we observe open up encouraging prospects for the use of magnetic nanoribbons in quantum spintronic devices

Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs

Connected components and spanning forest are fundamental graph algorithms due to their use in many important applications, such as graph clustering and image segmentation. GPUs are an ideal platform for graph algorithms due to their high peak performance and memory bandwidth. While there exist several GPU connectivity algorithms in the literature, many design choices have not yet been explored. In this paper, we explore various design choices in GPU connectivity algorithms, including sampling, linking, and tree compression, for both the static as well as the incremental setting. Our various design choices lead to over 300 new GPU implementations of connectivity, many of which outperform state-of-the-art. We present an experimental evaluation, and show that we achieve an average speedup of 2.47x speedup over existing static algorithms. In the incremental setting, we achieve a throughput of up to 48.23 billion edges per second. Compared to state-of-the-art CPU implementations on a 72-core machine, we achieve a speedup of 8.26--14.51x for static connectivity and 1.85--13.36x for incremental connectivity using a Tesla V100 GPU

Methodological Considerations in Life Course Theory Research

Currently, disability studies is starting to apply a life course theory framework to some of its investigations. Given the strengths of each field, life course theory can greatly impact disability studies, and vice versa. For this cross pollination to reach its maximum potential, disability studies researchers need to understand life course methodology and the types of results that arise from these methods, as well as the implications of these results for the field of disability studies. This paper reviews life course methods as they apply to the field of disability studies. More specifically, methodological issues are highlighted through a study of individuals with traumatic brain injuries. The article illustrates the utility of life course theory as a tool to investigate the total life experiences of persons with disabilities and the implications of integrating non normative experiences into life course research