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cture with application to high-dimensional pattern recognition. In Biologically Inspired Cognitive Architec- tures, 2009. AAAI Press, 2009. ARKO9. I. Arel, D. Rose, and T. Karnowski. A deep learning architecture comprising homogeneous cortical circuits for scalable spatiotemporal pattern inference. NIP
m's memory of what it's useful to pay attention to, in what contexts. In CogPrime this is managed by the attention allocation subsystem. • Backward Chainer: A piece of software, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Concretely-Implemented Mind D
Ami89. Daniel J. Amit. Modeling brain function - the world of attractor neural networks. Cambridge University Press, New York, USA, 1989. ARC09. I. Arel, D. Rose, and R. Coop. Destin: A scalable deep learning architecture with application to high-dimensional robust pattern recognition. Proc. AAA! Wor
m's memory of what it's useful to pay attention to, in what contexts. In CogPrime this is managed by the attention allocation subsystem. • Backward Chainer: A piece of software, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. • CIM-Dynamic: Concretely-Implemented Mind D
1. Ami89. Daniel J. Amit. Modeling brain function — the world of attractor neural networks. Cambridge University Press, New York, USA, 1989. ARCO9. I. Arel, D. Rose, and R. Coop. Destin: A scalable deep learning architecture with application to high-dimensional robust pattern recognition. Proc. AAAI Work
stem’s memory of what it’s useful to pay attention to, in what contexts. In CogPrime this is managed by the attention allocation subsystem. Backward Chainer: A piece of software, wrapped in a MindAgent, that carries out back- ward chaining inference using PLN. CIM-Dynamic: Concretely-Implemented Mind Dyn
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ORGANIZATIONOpenCog/PLN TruthValue
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