GeneRec

	GeneRec GeneRec is a generalization of the recirculation algorithm, and approximates Almeida-Pineda recurrent backpropagation.O'Reilly, R.C. Biologically Plausible Error-driven Learning using Local Activation Differences: The Generalized Recirculation Algorithm. Neural Computation, 8, 895–938Abstract It is used as part of the Leabra algorithm for error-driven learning. The symmetric, midpoint version of GeneRec is equivalent to the contrastive Hebbian learning algorithm (CHL). See also * Leabra Leabra stands for local, error-driven and associative, biologically realistic algorithm. It is a model of learning which is a balance between Hebbian and error-driven learning with other network-derived characteristics. This model is used to mathe ... O'Reilly (1996; Neural Computation) References Neuroscience Machine learning algorithms {{neuroscience-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Leabra Leabra stands for local, error-driven and associative, biologically realistic algorithm. It is a model of learning which is a balance between Hebbian and error-driven learning with other network-derived characteristics. This model is used to mathematically predict outcomes based on inputs and previous learning influences. This model is heavily influenced by and contributes to neural network designs and models. This algorithm is the default algorithm in ''emergent'' (successor of PDP++) when making a new project, and is extensively used in various simulations. Hebbian learning is performed using conditional principal components analysis (CPCA) algorithm with correction factor for sparse expected activity levels. Error-driven learning is performed using GeneRec, which is a generalization of the recirculation algorithm, and approximates Almeida–Pineda recurrent backpropagation. The symmetric, midpoint version of GeneRec is used, which is equivalent to the contrastive Hebbian learn ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Error-driven Learning Error-driven learning is a sub-area of machine learning concerned with how an Intelligent agent, agent ought to take actions in an Environment (biophysical), environment so as to minimize some error feedback. It is a type of reinforcement learning. Algorithms * GeneRec Machine learning algorithms {{Compu-AI-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Recirculation Algorithm Circulation may refer to: Science and technology * Atmospheric circulation, the large-scale movement of air * Circulation (physics), the path integral of the fluid velocity around a closed curve in a fluid flow field * Circulatory system, a biological organ system whose primary function is to move substances to and from cells * Circulation problem, a generalization of network flow problems * Circulation (architecture), the flow of people through a building * Circulation (currency), all currency held by consumers and businesses, but not by financial institutions and governments * Exhaust gas recirculation, a nitrogen oxide reduction technique used in most gasoline and diesel engines * Library circulation, the activities around the lending of library books and other material to users of a lending library * Rhetorical circulation, the ways that texts and discourses move through time and space Other uses * Newspaper circulation, the average number of copies of a newspaper distributed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Contrastive Hebbian Learning Contrastive Hebbian learning is a biologically plausible form of Hebbian learning. It is based on the contrastive divergence algorithm, which has been used to train a variety of energy-based latent variable models. In 2003, contrastive Hebbian learning was shown to be equivalent in power to the backpropagation algorithms commonly used in machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine .... References See also * Oja's rule * Generalized Hebbian algorithm Hebbian theory Artificial neural networks {{computing-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Neuroscience Neuroscience is the scientific study of the nervous system (the brain, spinal cord, and peripheral nervous system), its functions and disorders. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, psychology, physics, computer science, chemistry, medicine, statistics, and Mathematical Modeling, mathematical modeling to understand the fundamental and emergent properties of neurons, glia and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "epic challenge" of the Biology, biological sciences. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales. The techniques used by neuroscientists have expanded enormously, from molecular biology, molecular and cell biology, cellular studies of individual neurons to neuroimaging, imaging ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]