Neurobots.com
Neurobots
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Neurobots are robots that use neural network structures to learn and adapt to their environment. Neurobots.com is currently an informational site concerning basic neurobot concepts and potential applications. Both organic and inorganic neural networks process information using highly parallel, distributed, probabilistic signal processing. Neurobots excel at design recognition problems that are not well addressed by the sequential processing of regular robots.
Adaptive neural evolution is the significant to knowledge in both organic and inorganic neural networks. Neural networks begin as a flexible, highly-randomized array of densely inter-connected signal processing neural units. Interaction between the neural network and its ecology changes the relative strength and boom of inter-connections and nodes. Connections that are confirmed by subsequent environmental interactions are reinforced and grow. Connections that are not confirmed are weakened and atrophy. This creates an adaptive loop between neural evolution and environmental realities. "Neural memory" is the integrated sum and system of information, learned associations among data, and information on the evolutionary process of knowledge itself stored within a neural network. "Neuram" is a particular form of neural memory that employs hybrid cyber-neural memory units obtained by either inorganic material processing instruments (such as computers) or biologic material processing organs (such as the human brain). A neurobot is a robot that is guided by an adaptive, evolutionary learning process using a virtual neural network or a computer-brain interface between inanimate circuitry and a living neural network. Rather than invention robots whose components and software are fully specified, researchers can construct neurobots with neural networks than can adapt and partially "program themselves."
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