Constraint Propagation for Efficient Inference in Markov Logic

2011 ◽  
pp. 691-705 ◽  
Author(s):  
Tivadar Papai ◽  
Parag Singla ◽  
Henry Kautz
Keyword(s):  
Constraint Propagation ◽  
Markov Logic

Review on Fog Based Spectrum Sensing for Artificial Intelligence

2018 ◽  
pp. 66-70
Author(s):  
A. Rethina Palin ◽  
I. Jeena Jacob
Keyword(s):  
Bandwidth Allocation ◽  
Situational Awareness ◽  
Cluster Head ◽  
Mesh Network ◽  
Network Systems ◽  
Markov Logic ◽  
Wireless Mesh ◽  
Local Environments ◽  
Reactive Routing ◽  
The Hierarchical Structure

Wireless Mesh Network (MWN) could be divided into proactive routing, reactive routing and hybrid routing, which must satisfy the requirements related to scalability, reliability, flexibility, throughput, load balancing, congestion control and efficiency. DMN (Directional Mesh Network) become more adaptive to the local environments and robust to spectrum changes. The existing computing units in the mesh network systems are Fog nodes, the DMN architecture is more economic and efficient since it doesn’t require architecture- level changes from existing systems. The cluster head (CH) manages a group of nodes such that the network has the hierarchical structure for the channel access, routing and bandwidth allocation. The feature extraction and situational awareness is conducted, each Fog node sends the information regarding the current situation to the cluster head in the contextual format. A Markov logic network (MLN) based reasoning engine is utilized for the final routing table updating regarding the system uncertainty and complexity.

scholarly journals Entity Resolution in Sparse Encounter Network Using Markov Logic Network

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Christian Lu ◽  
Guangyan Huang ◽  
Yong Xiang.
Keyword(s):  
Entity Resolution ◽  
Markov Logic ◽  
Logic Network ◽  
Markov Logic Network

Application of Constraint Propagation in Part Family Modelling

CIRP Annals ◽  
1994 ◽  
Vol 43 (1) ◽  
pp. 129-132 ◽  
Author(s):  
Martti Mäntylä ◽  
Krista Lagus ◽  
Timo Laakko ◽  
Gunnar Sohlenius
Keyword(s):  
Constraint Propagation ◽  
Part Family

Liver tumors segmentation from CTA images using voxels classification and affinity constraint propagation

2010 ◽  
Vol 6 (2) ◽  
pp. 247-255 ◽  
Author(s):  
Moti Freiman ◽  
Ofir Cooper ◽  
Dani Lischinski ◽  
Leo Joskowicz
Keyword(s):  
Liver Tumors ◽  
Constraint Propagation

Dimensional analysis and constraint propagation systems applied to the design of electromagnetic devices

2000 ◽  
Vol 36 (4) ◽  
pp. 1673-1676 ◽  
Author(s):  
D.A. Lowther ◽  
G. Saxena ◽  
Y.K. Wong ◽  
A. Almaghrawi
Keyword(s):  
Dimensional Analysis ◽  
Constraint Propagation ◽  
Electromagnetic Devices

Proving the Labeled Interval Calculus for Inferences on Catalogs

1990 ◽  
Author(s):  
Walid Habib ◽  
Allen C. Ward
Keyword(s):  
Mechanical Design ◽  
Formal System ◽  
Constraint Propagation ◽  
Operating Conditions ◽  
Manufacturing Processes ◽  
Entire System ◽  
High Level Language ◽  
Design Problems ◽  
High Level ◽  
Interval Constraint

Abstract The “labeled interval calculus” is a formal system that performs quantitative inferences about sets of artifacts under sets of operating conditions. It refines and extends the idea of interval constraint propagation, and has been used as the basis of a program called a “mechanical design compiler,” which provides the user with a “high level language” in which design problems for systems to be built of cataloged components can be quickly and easily formulated. The compiler then selects optimal combinations of catalog numbers. Previous work has tested the calculus empirically, but only parts of the calculus have been proven mathematically. This paper presents a new version of the calculus and shows how to extend the earlier proofs to prove the entire system. It formalizes the effects of toleranced manufacturing processes through the concept of a “selectable subset” of the artifacts under consideration. It demonstrates the utility of distinguishing between statements which are true for all artifacts under consideration, and statements which are merely true for some artifact in each selectable subset.

Knowledge Based Expert Systems for CAD/CAM Experience of an EDM Application

1993 ◽  
Author(s):  
D. Kiritsis ◽  
Michel Porchet ◽  
L. Boutzev ◽  
I. Zic ◽  
P. Sourdin
Keyword(s):  
Natural Language ◽  
System Development ◽  
Constraint Propagation ◽  
Programming Environment ◽  
Knowledge Based ◽  
Natural Language Programming ◽  
Cad Cam ◽  
The One ◽  
Rule System ◽  
Cam Systems

Abstract In this paper we present our experience from the use of two different expert system development environments to Wire-EDM CAD/CAM knowledge based application. The two systems used follow two different AI approaches: the one is based on the constraint propagation theory and provides a natural language oriented programming environment, while the other is a production rule system with backward-forward chaining mechanisms and a conventional-like programming style. Our experience showed that the natural language programming style offers an easier and more productive environment for knowledge based CAD/CAM systems development.

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