Optimizing Intelligent Agent’s Constraint Satisfaction with Neural Networks

2003 ◽  
pp. 255-272
Author(s):  
Arpad Kelemen ◽  
Yulan Liang ◽  
Robert Kozma ◽  
Stan Franklin
Keyword(s):  
Neural Networks ◽  
Constraint Satisfaction

scholarly journals Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective

2020 ◽  
Author(s):  
Luís C. Lamb ◽  
Artur d’Avila Garcez ◽  
Marco Gori ◽  
Marcelo O.R. Prates ◽  
Pedro H.C. Avelar ◽  
...  
Keyword(s):  
Neural Networks ◽  
Constraint Satisfaction ◽  
State Of The Art ◽  
Relational Reasoning ◽  
Widespread Application ◽  
Symbolic Computing ◽  
Industry Research ◽  
Optimization Constraint ◽  
The Subject ◽  
Graph Neural Networks

Neural-symbolic computing has now become the subject of interest of both academic and industry research laboratories. Graph Neural Networks (GNNs) have been widely used in relational and symbolic domains, with widespread application of GNNs in combinatorial optimization, constraint satisfaction, relational reasoning and other scientific domains. The need for improved explainability, interpretability and trust of AI systems in general demands principled methodologies, as suggested by neural-symbolic computing. In this paper, we review the state-of-the-art on the use of GNNs as a model of neural-symbolic computing. This includes the application of GNNs in several domains as well as their relationship to current developments in neural-symbolic computing.

Constraint Satisfaction Neural Networks

1998 ◽  
Vol 33 (2) ◽  
pp. 389-408 ◽  
Author(s):  
Massimo Buscema
Keyword(s):  
Neural Networks ◽  
Constraint Satisfaction

Neural Networks for Constraint Satisfaction

1993 ◽  
Vol 5 (2) ◽  
pp. 169-187
Author(s):  
ANGELO MONFROGLIO
Keyword(s):  
Neural Networks ◽  
Constraint Satisfaction

CONSTRAINT SATISFACTION NEURAL NETWORKS FOR IMAGE SEGMENTATION

1991 ◽  
pp. 1087-1090 ◽  
Author(s):  
Wei-Chung Lin ◽  
Eric Chen-Kuo Tsao ◽  
Chin-Tu Chen
Keyword(s):  
Neural Networks ◽  
Image Segmentation ◽  
Constraint Satisfaction
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