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Machine learningNeuroevolution

NEAT: NeuroEvolution of Augmenting Topologies

NEAT ni algorithmu hisia kwa ajili ya kubadilisha mitandao bandia ya neva iliyoanzishwa na Kenneth Stanley na Risto Miikkulainen mwaka 2002. Tofauti na mbinu zinazobadilisha uzito pekee, NEAT hubadilisha kwa wakati mmoja muundo (topologia) na uzito wa miunganisho wa mitandao ya neva. Inafanikisha hili kupitia usimbaji moja kwa moja wa jenomu wenye alama za kihistoria zinazowezesha mchanganyiko wenye maana kati ya mitandao yenye miundo tofauti, na kuifanya ifae kwa ujifunzaji wa uimarishaji, uchezaji wa michezo, na kazi za udhibiti bila kuhitaji usanifu uliowekwa mapema.

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Vyanzo

  1. Stanley, K. O., & Miikkulainen, R. (2002). Evolving neural networks through augmenting topologies. Evolutionary Computation, 10(2), 99–127. DOI: 10.1162/106365602320169811

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 2). NeuroEvolution of Augmenting Topologies (NEAT). ScholarGate. https://scholargate.app/sw/deep-learning/neat

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ScholarGateNEAT (NeuroEvolution of Augmenting Topologies (NEAT)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/neat · Seti ya data: https://doi.org/10.5281/zenodo.20539026