Handbook of Neural Network Signal Processing
Handbook of Neural Network Signal Processing
Graphical Models: Foundations of Neural Computation
Graphical Models: Foundations of Neural Computation
The Harmonic Mind: From Neural Computation to Optimality-Theoretic GrammarVolume I: Cognitive Architecture (Bradford Books)
Markov Random Field Modeling in Image Analysis
Markov Random Field Modeling in Image Analysis
Extending the Soar Cognitive Architecture
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
Markov Logic: An Interface Layer for Artificial Intelligence
Markov Logic: An Interface Layer for Artificial Intelligence
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Rethinking cognitive architecture via graphical models
Cognitive Systems Research
From memory to problem solving: mechanism reuse in a graphical cognitive architecture
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Extending mental imagery in sigma
AGI'12 Proceedings of the 5th international conference on Artificial General Intelligence
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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.