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Hybrid Connectionist-Symbolic Modules: A Report from the IJCAI-95 Workshop on Connectionist-Symbolic Integration
1996
The AI Magazine
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The general consensus was that hybrid connectionist-symbolic models constitute a promising avenue to the development of more robust, more powerful, and more versatile architectures for both cognitive modeling ...
The focus of the workshop was on learning and architectures that feature hybrid representations and support hybrid learning. ...
Acknowledgment I want to thank Frederic Alexandre, Michael Dyer, John Barnden, Larry Bookman, Noel Sharkey, Jim Hendler, and other members of the committee for their roles in organizing this workshop. ...
doi:10.1609/aimag.v17i2.1225
dblp:journals/aim/Sun96
fatcat:gfqhf6cfmrdxddsazbaqkwf3qq
Dimensions of Neural-symbolic Integration - A Structured Survey
[article]
2005
arXiv
pre-print
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In particular the understanding of ways to deal with symbolic knowledge within connectionist systems (also called artificial neural networks) has reached a critical mass which enables the community to ...
We present a comprehensive survey of the field of neural-symbolic integration, including a new classification of system according to their architectures and abilities. ...
Local versus Distributed Representation of Knowledge For integrated neural-symbolic systems, the question is crucial how symbolic knowledge is represented within the connectionist system. ...
arXiv:cs/0511042v1
fatcat:wh4bv3oo35akncg3ds6djkws3m
The Present and the Future of Hybrid Neural Symbolic Systems: Some Reflections from the NIPS Workshop
2001
The AI Magazine
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In Feldman and Bailey's talk, it was proposed that there are the following distinct levels: cognitive linguistic, computational, structured connectionist, computational biological, and biological. ...
In terms of the relation between symbolic and neural knowledge during learning, we have the following possibilities: (1) purely neural learning of symbolic knowledge (for example,
The Present and the ...
Sun's research interest centers on the studies of intelligence and cognition, especially in the areas of commonsense reasoning, human and machine learning, and hybrid connectionist models. ...
doi:10.1609/aimag.v22i1.1551
dblp:journals/aim/WermterS01
fatcat:hhoutpiucbfebmwwxxwukctkgu
Representational Issues in the Debate on the Standard Model of the Mind
[article]
2018
arXiv
pre-print
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Finally, we briefly analyze the alternative representational assumptions employed in the three CAs constituting the current baseline for the Standard Model (i.e. SOAR, ACT-R and Sigma). ...
In doing so we outline some of the main problems affecting the current CAs and suggest that the Conceptual Spaces, a representational framework developed by Gardenfors, is worth-considering to address ...
Some of them adopt a symbolic approach, some are based on a purely connectionist model, while others adopt a hybrid approach combining connectionist and symbolic representational levels. ...
arXiv:1804.08299v1
fatcat:pjiaibsa2ff3zkdlogo53jjg2e
A component-based architecture for flexible integration of robotic systems
2010
2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
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The formal underpinnings and perceptual processes are described in the context of a biohazard detection task. ...
The architecture is based on the conceptual spaces representation that Gärdenfors suggested as an alternative to more traditional AI approaches. ...
However, classical knowledge representations (e.g., symbolic representations and connectionist methods) have several deficits such as the frame and symbol grounding problems, and can exhibit difficulty ...
doi:10.1109/iros.2010.5652394
dblp:conf/iros/JungDK10
fatcat:roe56akfqfdmldhnra7zsorog4
Knowledge Processing
1996
IMIA Yearbook of Medical Informatics
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Hybrid connectionist expert systems were, therefore, proposed, integrating symbolic and connectionist paradigms, both supporting each other. ...
This paradigm is based on a distributed object environment with services and brokers to handle integration with different and heterogeneous applications. ...
doi:10.1055/s-0038-1638062
fatcat:c2lmhk2i2zabdgzcbm7rmuc42i
The knowledge level in cognitive architectures: Current limitations and possible developments
2018
Cognitive Systems Research
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In this paper we identify and characterize an analysis of two problematic aspects affecting the representational level of cognitive architectures (CAs): the size and the typology of the encoded knowledge ...
representation and processing mechanisms with those executed by humans in their everyday activities. ...
The integration of ACT-R18
mechanisms to a symbolic knowledge base. ...
doi:10.1016/j.cogsys.2017.05.001
fatcat:ze4iluck3fabtiz7zwy4qbzuha
Knowledge graph using resource description framework and connectionist theory
2020
Journal of Physics, Conference Series
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The weighted RDF in Graph Neural Network will represent the knowledge graph using RDF and connectionist theory. ...
Interest in Knowledge Graph has peeked these years. ...
Motivation The connectionist or sub-symbolic approaches employing artificial neural network fundamentally differs from the symbolic approaches that use logic and reasoning in a knowledge graph. ...
doi:10.1088/1742-6596/1427/1/012001
fatcat:uqnd3tliczdhtarlu256inzjtu
Reasoning with Deep Learning: an Open Challenge
2016
International Conference of the Italian Association for Artificial Intelligence
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In particular, providing an effective integration of learning and reasoning mechanisms is a long-standing research problem at the intersection of many different areas, such as machine learning, cognitive ...
neuroscience, psychology, linguistic, and logic. ...
Pioneering approaches Throughout the years, there have been many attempts to combine learning and reasoning processes by integrating connectionist and symbolic paradigms. ...
dblp:conf/aiia/Lippi16
fatcat:bygkeanwrnhnrp645eqtd5vx3m
User-centered visual analysis using a hybrid reasoning architecture for intensive care units
2012
Decision Support Systems
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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. ...
The computation module is a neuro-symbolic engine for medical knowledge representation and reasoning. ...
doi:10.1016/j.dss.2012.06.009
fatcat:lm3j7jy3sbathfwbl4dmlqzwui
Editorial Commentary
1988
Behavioral and Brain Sciences
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The level of analysis is intermediate between those of symbolic cognitive models and neural models. ...
Higher-level analyses of these connectionist models reveal subtle relations to symbolic models. ...
To say that knowledge in a connectionist computer program is manifest within a system of weights and differential equations is not only a retreat from symbolic meaning representation, it's a retreat from ...
doi:10.1017/s0140525x00052791
fatcat:7o7kyja25jfztfovklj74nqt3y
Representational Limits in Cognitive Architectures
2016
EUCognition
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As a possible way out to face, jointly, these problems, this contribution discusses the possibility of integrating external, but architecturally compliant, cognitive systems into the knowledge representation ...
In particular, it addresses the problems regarding both the limited size and the homogeneous typology of the encoded (and processed) conceptual knowledge. ...
The arguments presented in this paper have been discussed in different occasions with Christian Lebiere, Alessandro Oltramari, Antonio Chella, Marcello Frixione, Peter Gärdenfors, Valentina Rho and Daniele ...
dblp:conf/eucognition/Lieto16
fatcat:tsl22lrhzrdhbmxlkmddtudt4i
Combining Data-Driven and Knowledge-Based AI Paradigms for Engineering AI-Based Safety-Critical Systems
2022
AAAI Conference on Artificial Intelligence
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The proposed paradigm recognizes existing AI approaches, namely connectionist, symbolic, and hybrid, and proffers to leverage their essential traits captured as knowledge. ...
A conceptual meta-body is thus obtained respectively containing categories for Data-, Knowledge-and Hybrid-driven. ...
More recently (Sun 2015), hybrid approaches integrating symbolic-based and connectionist paradigms have been proposed. ...
dblp:conf/aaai/MattioliPKL22
fatcat:b6yflydkjravvjg6cqe3ygwnni
Framework of fully integrated hybrid systems
2011
Neural computing & applications (Print)
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Tightly coupled systems include common representation structures which allow two-directional information exchanges between connectionist and symbolic modules enabling parallel processing. ...
On the other hand, a master-slave kind of configuration between the connectionist and the symbolic modules does not facilitate a thorough integration. ...
doi:10.1007/s00521-011-0672-9
fatcat:qaaujnjc3jfbvfbwqinrgeaide
Indispensability of Computational Modeling in Cognitive Science
2012
Journal of Cognitive Science
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-symbolic, connectionist, dynamic and probabilistic. ...
The concept of computation remains a frequently discussed topic in cognitive science, but there is no consensus about its meaning and the role in this field. ...
Connectionist, dynamical and probabilistic approaches may become in the future more integrated within the computational cognitive science (McClelland, 2009 ). ...
doi:10.17791/jcs.2012.13.4.401
fatcat:fxr4sbkcbbhijmfecyo2tgvps4
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