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A Dual Process Architecture for Ontology-based Systems

Antonio Lieto, Andrea Minieri, Alberto Piana, Daniele P. Radicioni, Marcello Frixione
2014 Proceedings of the International Conference on Knowledge Engineering and Ontology Development  
In this work we present an ontology-based system equipped with a hybrid architecture for the representation of conceptual information.  ...  The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science and the dual process theories of reasoning and rationality.  ...  -including cognitive architectures such as, for example, CLAR-ION 9 -, in which the connectionist component is used to model fast, associative processes, while the symbolic component is responsible for  ... 
doi:10.5220/0005070800480055 dblp:conf/ic3k/LietoMPRF14 fatcat:5wlmoafstzcthf2gfawtfmxyge

SEMANTIC IMAGE ANALYSIS USING A SYMBOLIC NEURAL ARCHITECTURE

Ilianna Kollia, Nikolaos Simou, Andreas Stafylopatis, Stefanos Kollias
2010 Image Analysis and Stereology  
This knowledge is transferred to a kernel based connectionist system, which is then adapted to a specific application field through extraction and use of MPEG-7 image descriptors.  ...  The proposed approach includes a formal knowledge component, which, assisted by a reasoning engine, generates the a-priori knowledge for the image analysis problem.  ...  THE PROPOSED ARCHITECTURE The proposed system is based on a learning, evolving and adapting cognitive model.  ... 
doi:10.5566/ias.v29.p159-172 fatcat:mlo2c6inhrbwthuxc2k35tqy24

Hypernetworks: A Molecular Evolutionary Architecture for Cognitive Learning and Memory

Byoung-Tak Zhang
2008 IEEE Computational Intelligence Magazine  
We then propose the recently-developed hypernetwork model as a candidate architecture for cognitive learning and memory.  ...  The chemically-based massive interaction for information organization and processing in the molecular hypernetworks, referred to as hyperinteractionism, is contrasted with the symbolist, connectionist,  ...  Processing involves syntaxbased sequential operations. (2) The connectionist paradigm models cognition as patterns of neural activity [14] , [66] .  ... 
doi:10.1109/mci.2008.926615 fatcat:dr23kuxnsnb2hayxjhf4r3hxbe

The ACT-R Cognitive Architecture and Its pyactr Implementation [chapter]

Adrian Brasoveanu, Jakub Dotlačil
2020 Language, Cognition, and Mind  
The term 'cognitive architecture' was first introduced by Bell and Newell (1971).  ...  Using a cognitive architecture can be very useful for the working linguist and psycholinguist, for the very same reasons.  ...  ACT-R's success in modeling linguistic phenomena is to a large extent attributable to the fact that ACT-R is a so-called hybrid cognitive architecture.  ... 
doi:10.1007/978-3-030-31846-8_2 fatcat:cav4xzojifbqjpm2irbm4ojijy

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges [article]

Denis Kleyko, Dmitri A. Rachkovskij, Evgeny Osipov, Abbas Rahimi
2022 arXiv   pre-print
This second part surveys existing applications, the role of HDC/VSA in cognitive computing and architectures, as well as directions for future work.  ...  Part I of this survey covered foundational aspects of the area, such as historical context leading to the development of HDC/VSA, key elements of any HDC/VSA model, known HDC/VSA models, and transforming  ...  The main problem with the APNN architecture is that not all its aspects have been modelled.  ... 
arXiv:2112.15424v2 fatcat:uteoq33hgna2fhs2o46rkde2iq

Universal Memory Architectures for Autonomous Machines [article]

Dan P. Guralnik, Daniel E. Koditschek
2015 arXiv   pre-print
cubical complexes, whose rich convexity theory underlies the planning cycle of the proposed architecture.  ...  The architecture is simple enough to ensure (1) a quadratic bound (in the number of available sensors) on space requirements, and (2) a quadratic bound on the time-complexity of the update-execute cycle  ...  ACKNOWLEDGEMENTS This work was funded in part by the Air Force Office of Science Research under the MURI FA9550-10-1-0567 and in part by the National Science Foundation under CDI-II-1028237.  ... 
arXiv:1502.06132v1 fatcat:26d6vgn7qbgfxl64xip6irhebu

Integrating Emotions in the TRIPLE ECA Model [chapter]

Kiril Kiryazov, Maurice Grinberg
2010 Lecture Notes in Computer Science  
Triple is a hybrid cognitive model consisting of three interacting modules -the reasoning, the connectionist, and the emotion enginesrunning in parallel.  ...  Emotions will increase the most important cognitive aspects of the model like context sensitivity, rich experiential episodic knowledge and anticipatory mechanisms.  ...  Acknowledgments This research was supported financially by the project RASCALLI (IST program, contract 27596), funded by the EC.  ... 
doi:10.1007/978-3-642-12397-9_10 fatcat:dvgybhkgbzgqfph3d2obwvrjxa

A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents

David Vernon, Giorgio Metta, Giulio Sandini
2007 IEEE Transactions on Evolutionary Computation  
systems, and also efforts to combine the two in hybrid systems.  ...  We then review several cognitive architectures drawn from these paradigms.  ...  ACKNOWLEDGMENT The authors would like to acknowledge the many helpful comments of the two anonymous referees on earlier versions of this paper.  ... 
doi:10.1109/tevc.2006.890274 fatcat:s3ueaficnjbebkrfnend4ahpau

Symbolic connectionism in natural language disambiguation

S.W.K. Chan, J. Franklin
1998 IEEE Transactions on Neural Networks  
This article will describe how to use the whole range of information through a neurosymbolic architecture which is a hybridization of a symbolic network and subsymbol vectors generated from a connectionist  ...  Index Terms-Bayesian network, constraint satisfaction, hybrid systems, natural language understanding, neural network applications, semantic analysis.  ...  The authors are also grateful to two of the anonymous reviewers for their valuable and constructive comments which really improved the paper from its previous versions.  ... 
doi:10.1109/72.712149 pmid:18255763 fatcat:jwqgdg3gcjatjiby7yezvuwfh4

Recursive distributed representations

Jordan B. Pollack
1990 Artificial Intelligence  
They form a bridge between the data structures necessary for high-level cognitive tasks and the associative, pattern recognition machinery provided by neural networks.  ...  The resulting representations are novel, in that they combine apparently immiscible aspects of features, pointers, and symbol structures.  ...  Hybrid (connectionist-symbolic) models [6] [7] [8] [9] have the potential for more powerful representations, but do not insist on the neural plausibility constraints which create the limitations in the  ... 
doi:10.1016/0004-3702(90)90005-k fatcat:2zbj6vjmsbf4ropnq2thz4gqla

Rethinking Eliminative Connectionism

Gary F. Marcus
1998 Cognitive Psychology  
This limitation might be avoided through the use of an architecture that implements symbol manipulation.  ...  Next, it is shown that the class of eliminative connectionist models that is currently popular cannot learn to extend universals outside the training space.  ...  Here the term hybrid really refers to a hybrid level of analysis rather than a hybrid cognitive architecture. 15 For a critique of the tensor representation of variables used by Halford et al. (1997  ... 
doi:10.1006/cogp.1998.0694 pmid:9892549 fatcat:h3yovqxxkvcovfoahg37dmpuky

Connectionist variable binding

Antony Browne, Ron Sun
1999 Expert systems  
Variable binding has long been a challenge to connectionists.  ...  Attempts to perform variable binding using localist and distributed connectionist representations are discussed, and problems inherent in each type of representation are outlined.  ...  and hybrid intelligent models.  ... 
doi:10.1111/1468-0394.00108 fatcat:s4krm3kzuzdebjvdskbcnqivjy

Distributed Symbol Discovery through Symbol Recirculation: Toward Natural Language Processing in Distributed Connectionist Networks [chapter]

2016 Connectionist Approaches to Natural Language Processing  
any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the  ...  British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-138-19163-1 (Set) ISBN: 978-1-315-54401-4 (Set) (ebk) ISBN: 978-1-138-  ...  A hybrid symbolic/connectionist model for noun phrase understanding. Connection Science, 1 (3), 255-275. Wilensky, R. (1978). Understanding goal-based stories. Ph.D.  ... 
doi:10.4324/9781315636863-15 fatcat:gndg4g4x2zhu3kl63hvxc6gxfa

Recurrent Neural Network Method in Arabic Words Recognition System [article]

Yusuf Perwej
2013 arXiv   pre-print
The key innovation is a recently produce recurrent neural networks objective function known as connectionist temporal classification.  ...  Because of the characteristic of the whole body of the Arabic words, namely connectivity between the characters, thereby the segmentation of An Arabic word is very difficult.  ...  CONNECTIONIST TEMPORAL CLASSIFICATION Connectionism within cognitive science is a theory of information processing.  ... 
arXiv:1301.4662v1 fatcat:bkovhn6bpvandkpl6qnyo7eob4

Categorial Compositionality II: Universal Constructions and a General Theory of (Quasi-)Systematicity in Human Cognition

Steven Phillips, William H. Wilson, Olaf Sporns
2011 PLoS Computational Biology  
A complete theory of cognitive architecture (i.e., the basic processes and modes of composition that together constitute cognitive behaviour) must explain the systematicity property-why our cognitive capacities  ...  ., aspects of most languages), where the domain includes some but not all possible combinations of constituents.  ...  Acknowledgments We thank the reviewers for thoughtful comments to help improve and clarify the exposition of this work. Author Contributions Wrote the manuscript: SP WW.  ... 
doi:10.1371/journal.pcbi.1002102 pmid:21857816 pmcid:PMC3154512 fatcat:pwvihnl3w5e3pgcxkusdbrfsmu
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