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| Titel: |
A Reinforcement Learning Model for Solving the Folding Problem |
| Auteur: |
Gabriela Czibula Maria Iuliona Bocicor Istran Gergely Czibula |
| Verschenen in: |
International journal of computer technology and applications |
| Paginering: | Jaargang 02 (2011) nr. 01 pagina's 171-182 |
| Jaar: |
2011 |
| Inhoud: |
In this paper we aim at proposing a reinforcement learning based model for solving combinatorial optimizationproblems. Combinatorial optimization problems are hardto solve optimally, that is why any attempt to improve theirsolutions is beneficent. We are particularly focusing onthe bidimensional protein folding problem, a well knownNP-hard optimizaton problem important within manyfields including bioinformatics, biochemistry, molecularbiology and medicine. A reinforcement learning model isintroduced for solving the problem of predicting the bidimensional structure of proteins in the hydrophobic-polarmodel. The model proposed in this paper can be easilyextended to solve other optimization problems. We also givea mathematical validation of the proposed reinforcementlearning based model, indicating this way the potential ofour proposal. |
| Uitgever: |
Technopark Publications (provided by DOAJ) |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 14 van 35 gevonden artikelen
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