6533b839fe1ef96bd12a6357
RESEARCH PRODUCT
ORGANIZED LEARNING MODELS (PURSUER CONTROL OPTIMISATION)
R. Plasubject
Computer Science::Machine LearningStochastic modellingActive learning (machine learning)business.industryDifferential equationPath (graph theory)Control (management)Online machine learningPursuerArtificial intelligenceState (computer science)businessMathematicsdescription
Abstract The concept of Organized Learning is defined, and some random models are presented. For Not Transferable Learning, it is necessary to start from an instantaneous learning; by a discrete way, we must form a stochastic model considering the probability of each path; with a continue aproximation, we can study the evolution of the internal state through to consider the relative and absolute probabilities, by means of differential equations systems. For Transferable Learning, the instantaneous learning give us directly the System evolution. So, the Algoritmes for the different models are compared.
year | journal | country | edition | language |
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1983-01-01 |