Results 31 to 40 of about 81,262 (253)
Studying Transaction Fees in the Bitcoin Blockchain with Probabilistic Logic Programming
Information, 2019 In Bitcoin, if a miner is able to solve a computationally hard problem called proof of work, it will receive an amount of bitcoin as a reward which is the sum of the fees for the transactions included in a block plus an amount inversely proportional to ...
Damiano Azzolini +2 more
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Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning
Frontiers in Big Data, 2020 Deep learning is bringing remarkable contributions to the field of argumentation mining, but the existing approaches still need to fill the gap toward performing advanced reasoning tasks.
Andrea Galassi +4 more
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Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring
Frontiers in Robotics and AI, 2020 Robotic agents should be able to learn from sub-symbolic sensor data and, at the same time, be able to reason about objects and communicate with humans on a symbolic level.
Pedro Zuidberg Dos Martires +5 more
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A Coalgebraic Perspective on Probabilistic Logic Programming [PDF]
, 2019 Probabilistic logic programming is increasingly important in artificial intelligence and related fields as a formalism to reason about uncertainty. It generalises logic programming with the possibility of annotating clauses with probabilities. This paper
Gu, Tao, Zanasi, Fabio
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Logical Methods in Computer ScienceMeasurable cones, with linear and measurable functions as morphisms, are a model of intuitionistic linear logic and of call-by-name probabilistic PCF which accommodates "continuous data types" such as the real line.
Thomas Ehrhard, Guillaume Geoffroy
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Preferential Cyber Defense for Power Grids
PRX Energy, 2023 The integration of computing and communication capabilities into the power grid has led to vulnerabilities enabling attackers to launch cyberattacks on the grid.
Mohammadamin Moradi +3 more
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The Functional Perspective on Advanced Logic Programming [PDF]
, 2016 The basics of logic programming, as embodied by Prolog, are generally well-known in the programming language community. However, more advanced techniques, such as tabling, answer subsumption and probabilistic logic programming fail to attract the ...
Vandenbroucke, Alexander
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On the Implementation of the Probabilistic Logic Programming Language ProbLog [PDF]
, 2009 The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have been developed.
ANGELIKA KIMMIG +23 more
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Learning hierarchical probabilistic logic programs [PDF]
Machine Learning, 2021 AbstractProbabilistic logic programming (PLP) combines logic programs and probabilities. Due to its expressiveness and simplicity, it has been considered as a powerful tool for learning and reasoning in relational domains characterized by uncertainty. Still, learning the parameter and the structure of general PLP is computationally expensive due to the
Nguembang Fadja A., Riguzzi F., Lamma E.
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Semantic Probabilistic Inference of Predictions
Известия Иркутского государственного университета: Серия "Математика", 2017 Prediction is one of the most important concepts in science. Predictions obtained from probabilistic knowledge, are described by an inductive-statistical inference (I-S inference).
E. E. Vityaev
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