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A Hybrid Neuro-Symbolic Approach for Complex Event Processing [article]

Marc Roig Vilamala, Harrison Taylor, Tianwei Xing, Luis Garcia, Mani Srivastava, Lance Kaplan, Alun Preece, Angelika Kimmig, Federico Cerutti
2020 arXiv   pre-print
We propose a hybrid neuro-symbolic architecture based on Event Calculus that can perform Complex Event Processing (CEP).  ...  It leverages both a neural network to interpret inputs and logical rules that express the pattern of the complex event.  ...  Conclusions In this paper we demonstrated the superiority of our approach against a feedforward neural architecture.  ... 
arXiv:2009.03420v3 fatcat:oen4x2hnsnhhtorwzzv62iz2ca

Modular design patterns for hybrid learning and reasoning systems

Michael van Bekkum, Maaike de Boer, Frank van Harmelen, André Meyer-Vitali, Annette ten Teije
2021 Applied intelligence (Boston)  
In this paper, we analyze a large body of recent literature and we propose a set of modular design patterns for such hybrid, neuro-symbolic systems.  ...  Recent years have seen a large number of publications on such hybrid neuro-symbolic AI systems.  ...  We have identified the need for a pattern-based system of systems approach towards design and evaluation of hybrid AI systems.  ... 
doi:10.1007/s10489-021-02394-3 fatcat:ecyruntfdncsbbtdglhllwc6vi

Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases [article]

Michael van Bekkum, Maaike de Boer, Frank van Harmelen, André Meyer-Vitali, Annette ten Teije
2021 arXiv   pre-print
In this paper we analyse a large body of recent literature and we propose a set of modular design patterns for such hybrid, neuro-symbolic systems.  ...  The main contributions of this paper are: 1) a taxonomically organised vocabulary to describe both processes and data structures used in hybrid systems; 2) a set of 15+ design patterns for hybrid AI systems  ...  for Scientific Research NWO, https://hybrid-intelligence-centre.nl.  ... 
arXiv:2102.11965v2 fatcat:uo5wj6gw2vc6dhgdrdt26wqslq

Neuro-Symbolic Artificial Intelligence: Current Trends [article]

Md Kamruzzaman Sarker, Lu Zhou, Aaron Eberhart, Pascal Hitzler
2021 arXiv   pre-print
Neuro-Symbolic Artificial Intelligence -- the combination of symbolic methods with methods that are based on artificial neural networks -- has a long-standing history.  ...  The article is meant to serve as a convenient starting point for research on the general topic.  ...  for delineation to hybrid systems; indeed the focus was entirely on integrated systems, where symbolic processing functionalities emerge from neural structures and processes.  ... 
arXiv:2105.05330v2 fatcat:4rmmoudmtvhbbhjpvuza6r4btm

Emulating the perceptual system of the brain for the purpose of sensor fusion

Rosemarie Velik, Roland Lang, Dietmar Bruckner, Tobias Deutsch
2008 2008 Conference on Human System Interactions  
Therefore, a new information processing principle called neuro-symbolic information processing is introduced.  ...  According to this method, sensory data are processed by so-called neuro-symbolic networks. The basic processing units of neuro-symbolic networks are neurosymbols.  ...  Function Principle of a Neuro-symbol Neuro-symbolic Networks To perform complex perceptive tasks, a certain number of neuro-symbols have to be interconnected.  ... 
doi:10.1109/hsi.2008.4581518 fatcat:2twynknjmram7dikbphyfqtmr4

Emulating the Perceptual System of the Brain for the Purpose of Sensor Fusion [chapter]

R. Velik, D. Bruckner, R. Lang, T. Deutsch
2009 Human-Computer Systems Interaction  
Therefore, a new information processing principle called neuro-symbolic information processing is introduced.  ...  According to this method, sensory data are processed by so-called neuro-symbolic networks. The basic processing units of neuro-symbolic networks are neurosymbols.  ...  Function Principle of a Neuro-symbol Neuro-symbolic Networks To perform complex perceptive tasks, a certain number of neuro-symbols have to be interconnected.  ... 
doi:10.1007/978-3-642-03202-8_2 fatcat:emyjhnvrzvbbjn5pungnoaxajm

Directions for Explainable Knowledge-Enabled Systems [article]

Shruthi Chari, Daniel M. Gruen, Oshani Seneviratne, Deborah L. McGuinness
2020 arXiv   pre-print
Recently, researchers have been investigating and tackling explainability with a user-centric focus, looking for explanations to consider trustworthiness, comprehensibility, explicit provenance, and context-awareness  ...  As Artificial Intelligence models have become more complex, and often more opaque, with the incorporation of complex machine learning techniques, explainability has become more critical.  ...  Neuro-Symbolic AI Methods Neuro-Symbolic integration is a hybrid field that marries inductive and statistical learning capabilities of ML methods with the symbolic and conceptual representation capabilities  ... 
arXiv:2003.07523v1 fatcat:mnsqhmeq6nfttirizkt5mipvwy

Neuro-symbolic Architectures for Context Understanding [article]

Alessandro Oltramari, Jonathan Francis, Cory Henson, Kaixin Ma, and Ruwan Wickramarachchi
2020 arXiv   pre-print
To combat these issues, we propose the use of hybrid AI methodology as a general framework for combining the strengths of both approaches.  ...  Specifically, we inherit the concept of neuro-symbolism as a way of using knowledge-bases to guide the learning progress of deep neural networks.  ...  Applications of Neuro-symbolism Application I: Learning a Knowledge Graph Embedding Space for Context Understanding in Automotive Driving Scenes Introduction Recently, there has been a significant  ... 
arXiv:2003.04707v1 fatcat:3bbg6kapvbcbnjkekqppin4bhm

Evaluation of the Performance of Telecommunication Systems by Approach of Hybrid Stochastic Automata Combined With Neuro-Fuzzy Networks

Offole Florence, Atangana Ateba, Kombe Timothée, Fohoue Kennedy
2017 European Scientific Journal  
The methodological approach consists in combining ANFIS neuro-fuzzy networks with hybrid stochastic automata.  ...  The Neuro-Fuzzy ANFIS networks provide a prediction for the passage from nominal mode to degraded mode, by controlling the occurrence of malfunctions at transient levels.  ...  Conclusion We have shown the relevance of our approach by integration of dynamic Hybrid Stochastic Automata, for the performance evaluation of the telecommunication system.  ... 
doi:10.19044/esj.2017.v13n18p498 fatcat:ocxsf3qr4fd73ch3aqlfy7vfuu

HySTER: A Hybrid Spatio-Temporal Event Reasoner [article]

Theophile Sautory, Nuri Cingillioglu, Alessandra Russo
2021 arXiv   pre-print
We present the HySTER: a Hybrid Spatio-Temporal Event Reasoner to reason over physical events in videos.  ...  Most methods designed for VideoQA up-to-date are end-to-end deep learning architectures which struggle at complex temporal and causal reasoning and provide limited transparency in reasoning steps.  ...  ILP learning tasks and would enable the model to build an interpretable cognitive model of the events in the scene from videos, perception, and background knowledge directly.  ... 
arXiv:2101.06644v1 fatcat:w36bjysdkjgtxdki6mujetdlpq

Deep Algorithmic Question Answering: Towards a Compositionally Hybrid AI for Algorithmic Reasoning [article]

Kwabena Nuamah
2021 arXiv   pre-print
We argue that the challenge of algorithmic reasoning in QA can be effectively tackled with a "systems" approach to AI which features a hybrid use of symbolic and sub-symbolic methods including deep neural  ...  system should possess, and conclude that they are best achieved with a combination of hybrid and compositional AI.  ...  The author would also like to thank reviewers for valuable feedback.  ... 
arXiv:2109.08006v3 fatcat:35ugb3qfdvg2djua7tvh4asll4

Soft computing and hybrid AI approaches to intelligent manufacturing [chapter]

László Monostori, József Hornyák, Csaba Egresits, Zsolt János Viharos
1998 Lecture Notes in Computer Science  
of a process started two decades ago.  ...  The fundamental aim of the paper is to outline the importance of soft computing and hybrid AI techniques in manufacturing by introducing a genetic algorithm (GA) based dynamic job shop scheduler and the  ...  Genetic algorithms for generation of neuro-fuzzy structures In [7? ] a neuro-fuzzy approach was introduced and its applications in manufacturing were described.  ... 
doi:10.1007/3-540-64574-8_463 fatcat:jwajdg6vfvfmnhvqqu4vk6c55u

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

Bernard Kamsu-Foguem, Germaine Tchuenté-Foguem, Laurent Allart, Youcef Zennir, Christian Vilhelm, Hossein Mehdaoui, Djamel Zitouni, Hervé Hubert, Mohamed Lemdani, Pierre Ravaux
2012 Decision Support Systems  
The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches  ...  We present a knowledge-and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods.  ...  Acknowledgments This work was partly funded by the European program FEDER, under the ISIS (Intelligent Survey for Information Systems) project.  ... 
doi:10.1016/j.dss.2012.06.009 fatcat:lm3j7jy3sbathfwbl4dmlqzwui

An Experimentation Platform for Explainable Coalition Situational Understanding [article]

Katie Barrett-Powell, Jack Furby, Liam Hiley, Marc Roig Vilamala, Harrison Taylor, Federico Cerutti, Alun Preece, Tianwei Xing, Luis Garcia, Mani Srivastava, Dave Braines
2020 arXiv   pre-print
and subsymbolic AI/ML approaches for event processing.  ...  We present an experimentation platform for coalition situational understanding research that highlights capabilities in explainable artificial intelligence/machine learning (AI/ML) and integration of symbolic  ...  Multimodal Explanations Complex Events The main approach we use for complex event detection in our work is a neuro-symbolic combination of neural network services to detect simple events and a symbolic  ... 
arXiv:2010.14388v2 fatcat:clysndaa6fgdbfclnfrippl2uy

Neuro-fuzzy rule generation: survey in soft computing framework

S. Mitra, Y. Hayashi
2000 IEEE Transactions on Neural Networks  
The neuro-fuzzy approach, symbiotically combining the merits of connectionist and fuzzy approaches, constitutes a key component of soft computing at this stage.  ...  To date, there has been no detailed and integrated categorization of the various neuro-fuzzy models used for rule generation.  ...  The neuro-fuzzy approach, which provides flexible information processing capability by devising methodologies and algorithms on a massively parallel system for representation and recognition of real-life  ... 
doi:10.1109/72.846746 pmid:18249802 fatcat:3y2gnxmiorbbfocd2pp7ygrwiy
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