Paper Info
Title
Implementing First-Order Variables in a Graphical Cognitive Architecture
Abstract
Graphical cognitive architectures implement their functionality through localized message passing among computationally limited nodes. First-order variables - particularly universally quantified ones - while critical for some potential architectural mechanisms, can be quite difficult to implement in such architectures. A new implementation strategy based on message decomposition in graphical models is presented that yields tractability while preserving key symmetries in the graphs concerning how quantified variables are represented and how symbols, probabilities and signals are processed.
Year
DOI
Venue
2010
10.3233/978-1-60750-660-7-119
BICA
Keywords
Field
DocType
first order,graphical model,cognitive architecture,message passing
Graph,Computer science,First order,Theoretical computer science,Artificial intelligence,Graphical model,Cognitive architecture,Cognition,Machine learning,Message passing
Conference
Volume
ISSN
Citations 
221
0922-6389
3
PageRank 
References 
Authors
0.53
5
1
Name
Order
Citations
PageRank
Paul S. Rosenbloom11416284.53