AMBIENTUM BIOETHICA BIOLOGIA CHEMIA DIGITALIA DRAMATICA EDUCATIO ARTIS GYMNAST. ENGINEERING EPHEMERIDES EUROPAEA GEOGRAPHIA GEOLOGIA HISTORIA HISTORIA ARTIUM INFORMATICA IURISPRUDENTIA MATHEMATICA MUSICA NEGOTIA OECONOMICA PHILOLOGIA PHILOSOPHIA PHYSICA POLITICA PSYCHOLOGIA-PAEDAGOGIA SOCIOLOGIA THEOLOGIA CATHOLICA THEOLOGIA CATHOLICA LATIN THEOLOGIA GR.-CATH. VARAD THEOLOGIA ORTHODOXA THEOLOGIA REF. TRANSYLVAN
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STUDIA INFORMATICA - Ediţia nr.4 din 2012 | |||||||
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A STUDY ON USING REINFORCEMENT LEARNING FOR TEMPORAL ORDERING OF BIOLOGICAL SAMPLES. Autori: . |
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Rezumat: The temporal ordering of biological samples, with the goal of retrieving the temporal evolution of dynamic biological processes, is an important problem within bioinformatics. As the general temporal ordering problem has been proven to be NP-complete, various approximation and heuristic methods are developed to approach it. Reinforcement Learning is an approach to machine intelligence in which an adaptive system can learn to behave in a certain way by receiving punishments or rewards for its chosen actions. This paper aims to investigate a reinforcement learning based approach to the temporal ordering problem and several variations to this approach, based on Q-Learning. The algorithms are experimentally evaluated on a time series gene expression data set and we provide analysis and comparisons of the obtained results. Key words and phrases. Bioinformatics, Temporal Ordering, Reinforcement Learning, Q-Learning. |
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