2018
Authors
Madeira, A; Benevides, M;
Publication
DALI@TABLEAUX
Abstract
2018
Authors
Benevides, MRF; Madeira, A; Martins, MA;
Publication
ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE
Abstract
Multi-Agent Epistemic Logic has been investigated in Computer Science [6] to represent and reason about agents or groups of agents knowledge and beliefs. Some extensions aimed to reasoning about knowledge and probabilities and also with a fuzzy semantics have been proposed [7,14]. This paper introduces a parametric method to build graded epistemic logics inspired in the systematic method to build Multi-valued Dynamic Logics introduced in [12,13]. The parameter in both methods is the same: an action lattice [10]. This algebraic structure supports a generic space of agent knowledge operators, as choice, composition and closure (as a Kleene algebra), but also a proper truth space for possible non bivalent interpretation of the assertions (as a residuated lattice).
2018
Authors
Benevides, M; Madeira, A;
Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
2018
Authors
Madeira, A;
Publication
Molecular Logic and Computational Synthetic Biology - First International Symposium, MLCSB 2018, Santiago, Chile, December 17-18, 2018, Revised Selected Papers
Abstract
This note, reporting the homonym keynote presented in the International Symposium on Molecular Logic and Computational Synthetic Biology 2018, traces an informal roadmap on Dynamic Logic (DL) field, focusing on its versatility and resilience to be adjusted and adopted in a wide class of application domains and computational paradigms. The exposition argues the room for developments on tagging DL to the analysis of synthetic biologic domain. © 2019, Springer Nature Switzerland AG.
2018
Authors
Maia, F; Mercier, H; Brito, A;
Publication
P2DS@EuroSys
Abstract
2018
Authors
Ribeiro, J; Machado, N; Maia, F; Matos, M;
Publication
Distributed Applications and Interoperable Systems - 18th IFIP WG 6.1 International Conference, DAIS 2018, Held as Part of the 13th International Federated Conference on Distributed Computing Techniques, DisCoTec 2018, Madrid, Spain, June 18-21, 2018, Proceedings
Abstract
Scalability is one of the most relevant features of today’s data management systems. In order to achieve high scalability and availability, recent distributed key-value stores refrain from costly replica coordination when processing requests. However, these systems typically do not perform well under churn. In this paper, we propose DataFlagons, a large-scale key-value store that integrates epidemic dissemination with a probabilistic total order broadcast algorithm. By ensuring that all replicas process requests in the same order, DataFlagons provides probabilistic strong data consistency while achieving high scalability and robustness under churn. © 2018, IFIP International Federation for Information Processing.
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