Results 1 to 10 of about 140,423 (144)
Coalgebraic Semantics for Probabilistic Logic Programming [PDF]
Logical Methods in Computer Science, 2021 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
Tao Gu, Fabio Zanasi
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On the Strong Equivalences for LPMLN Programs [PDF]
Logical Methods in Computer Science, 2021 LPMLN is a powerful knowledge representation and reasoning tool that combines the non-monotonic reasoning ability of Answer Set Programming (ASP) and the probabilistic reasoning ability of Markov Logic Networks (MLN).
Bin Wang +3 more
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Logic + probabilistic programming + causal laws
Royal Society Open Science, 2023 Probabilistic planning attempts to incorporate stochastic models directly into the planning process, which is the problem of synthesizing a sequence of actions that achieves some objective for a putative agent.
Vaishak Belle
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Probabilistic Logic Models for the Lightning Network
Cryptography, 2022 The Lightning Network (LN) has emerged as one of the prominent solutions to overcome the biggest limit of blockchain based on PoW: scalability. LN allows for creating a layer on top of an existing blockchain where users can send payments and micro ...
Damiano Azzolini, Fabrizio Riguzzi
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Optimizing Probabilities in Probabilistic Logic Programs [PDF]
Theory and Practice of Logic Programming 21 (2021) 543-556, 2021 Probabilistic Logic Programming is an effective formalism for encoding problems characterized by uncertainty. Some of these problems may require the optimization of probability values subject to constraints among probability distributions of random variables.
arxiv +1 more source
Developing an optimization model for prioritizing and selecting project risk response strategies [PDF]
Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī, 2023 Projects, during their execution, face various risks that can impact the achievement of project objectives. Therefore, the need for extensive project risk management is widely recognized.
Ali Namazian, Somayeh Behboodian
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Intention Recognition With ProbLog
Frontiers in Artificial Intelligence, 2022 In many scenarios where robots or autonomous systems may be deployed, the capacity to infer and reason about the intentions of other agents can improve the performance or utility of the system.
Gary B. Smith +6 more
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Meta-analysis of the functional neuroimaging literature with probabilistic logic programming
Scientific Reports, 2022 Inferring reliable brain-behavior associations requires synthesizing evidence from thousands of functional neuroimaging studies through meta-analysis.
Majd Abdallah +3 more
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Probabilistic call by push value [PDF]
Logical Methods in Computer Science, 2019 We introduce a probabilistic extension of Levy's Call-By-Push-Value. This extension consists simply in adding a " flipping coin " boolean closed atomic expression. This language can be understood as a major generalization of Scott's PCF encompassing both
Thomas Ehrhard, Christine Tasson
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eLife, 2022 The lateral prefrontal cortex (LPFC) of humans enables flexible goal-directed behavior. However, its functional organization remains actively debated after decades of research.
Majd Abdallah +3 more
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