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Relevant bibliographies by topics / Event Detection, Event Calculus, Answer Set Programming

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Journal articles
Dissertations / Theses
Book chapters
Conference papers

Academic literature on the topic 'Event Detection, Event Calculus, Answer Set Programming'

Author: Grafiati

Published: 10 March 2023

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Journal articles on the topic "Event Detection, Event Calculus, Answer Set Programming"

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Lee, J., and R. Palla. "Reformulating the Situation Calculus and the Event Calculus in the General Theory of Stable Models and in Answer Set Programming." Journal of Artificial Intelligence Research 43 (April 24, 2012): 571–620. http://dx.doi.org/10.1613/jair.3489.

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Circumscription and logic programs under the stable model semantics are two well-known nonmonotonic formalisms. The former has served as a basis of classical logic based action formalisms, such as the situation calculus, the event calculus and temporal action logics; the latter has served as a basis of a family of action languages, such as language A and several of its descendants. Based on the discovery that circumscription and the stable model semantics coincide on a class of canonical formulas, we reformulate the situation calculus and the event calculus in the general theory of stable mode

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ARIAS, JOAQUÍN, MANUEL CARRO, ZHUO CHEN, and GOPAL GUPTA. "Modeling and Reasoning in Event Calculus using Goal-Directed Constraint Answer Set Programming." Theory and Practice of Logic Programming 22, no. 1 (2021): 51–80. http://dx.doi.org/10.1017/s1471068421000156.

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AbstractAutomated commonsense reasoning (CR) is essential for building human-like AI systems featuring, for example, explainable AI. Event calculus (EC) is a family of formalisms that model CR with a sound, logical basis. Previous attempts to mechanize reasoning using EC faced difficulties in the treatment of the continuous change in dense domains (e.g. time and other physical quantities), constraints among variables, default negation, and the uniform application of different inference methods, among others. We propose the use of s(CASP), a query-driven, top-down execution model for Predicate

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Hall, Brendan, Sarat Chandra Varanasi, Jan Fiedor, et al. "Knowledge-Assisted Reasoning of Model-Augmented System Requirements with Event Calculus and Goal-Directed Answer Set Programming." Electronic Proceedings in Theoretical Computer Science 344 (September 13, 2021): 79–90. http://dx.doi.org/10.4204/eptcs.344.6.

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Meli, Daniele, Mohan Sridharan, and Paolo Fiorini. "Inductive learning of answer set programs for autonomous surgical task planning." Machine Learning 110, no. 7 (2021): 1739–63. http://dx.doi.org/10.1007/s10994-021-06013-7.

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AbstractThe quality of robot-assisted surgery can be improved and the use of hospital resources can be optimized by enhancing autonomy and reliability in the robot’s operation. Logic programming is a good choice for task planning in robot-assisted surgery because it supports reliable reasoning with domain knowledge and increases transparency in the decision making. However, prior knowledge of the task and the domain is typically incomplete, and it often needs to be refined from executions of the surgical task(s) under consideration to avoid sub-optimal performance. In this paper, we investigat

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KATZOURIS, NIKOS, GEORGIOS PALIOURAS, and ALEXANDER ARTIKIS. "Online Learning Probabilistic Event Calculus Theories in Answer Set Programming." Theory and Practice of Logic Programming, August 1, 2021, 1–25. http://dx.doi.org/10.1017/s1471068421000107.

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Abstract Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. Logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event pattern authoring. We present a system based on Answer Set Programming (ASP), capable of probabilistic reasoning with complex event patterns in the form of weighted rules in the Event Calculus, whose structure and weights are learnt onl

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Dissertations / Theses on the topic "Event Detection, Event Calculus, Answer Set Programming"

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Berreby, Fiona. "Models of Ethical Reasoning." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS137.

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Cette thèse s’inscrit dans le cadre du projet ANR eThicAa, dont les ambitions ont été : de définir ce que sont des agents autonomes éthiques, de produire des représentations formelles des conflits éthiques et de leurs objets (au sein d’un seul agent autonome, entre un agent autonome et le système auquel il appartient, entre un agent autonome et un humain, entre plusieurs agents autonomes) et d’élaborer des algorithmes d’explication pour les utilisateurs humains. L’objet de la thèse plus particulièrement a été d’étudier la modélisation de conflits éthiques au sein d’un seul agent, ainsi que la

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khan, Abdullah. "Event Detection in Videos." Doctoral thesis, 2020. http://hdl.handle.net/2158/1206034.

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In this age of the digital era, the rapid growth of video content is a common trend. Automated analysis for video content understanding is one of the most challenging and well researched area in the domain of artificial intelligence. In this thesis, we address this issue by analyzing and detecting events in videos. The automatic recognition of events in videos can be formally defined as: "detecting interactions between human-object, object-object or human-human activity in a certain scene". Such events are often referred to as simple events, whereas, complex event detection is even more d

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Book chapters on the topic "Event Detection, Event Calculus, Answer Set Programming"

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Arias, Joaquín, Zhuo Chen, Manuel Carro, and Gopal Gupta. "Modeling and Reasoning in Event Calculus Using Goal-Directed Constraint Answer Set Programming." In Logic-Based Program Synthesis and Transformation. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45260-5_9.

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Conference papers on the topic "Event Detection, Event Calculus, Answer Set Programming"

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Katzouris, Nikos, and Alexander Artikis. "WOLED: A tool for Online Learning Weighted Answer Set Rules for Temporal Reasoning Under Uncertainty." In 17th International Conference on Principles of Knowledge Representation and Reasoning {KR-2020}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/kr.2020/81.

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Abstract:

Complex Event Recognition (CER) systems detect event occurrences in streaming time-stamped input using predefined event patterns. Logic-based approaches are of special interest in CER, since, via Statistical Relational AI, they combine uncertainty-resilient reasoning with time and change, with machine learning, thus alleviating the cost of manual event pattern authoring. We present WOLED, a system based on Answer Set Programming (ASP), capable of probabilistic reasoning with complex event patterns in the form of weighted rules in the Event Calculus, whose structure and weights are learnt onlin

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