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    JGraphs: A Toolset to Work with Monte-Carlo Tree Search-Based Algorithms

    Autor: 
    García-Díaz, Vicente
    ;
    Núñez-Valdez, Edward Rolando
    ;
    González García, Cristian
    ;
    Gómez Gómez, Alberto
    ;
    González-Crespo, Rubén (1)
    Fecha: 
    12/2020
    Palabra clave: 
    Monte-Carlo; Monte-Carlo Tree Search; best-first search algorithm; combinatorial game; Tic-Tac-Toe; JGraphs; JCR; Scopus
    Tipo de Ítem: 
    Articulo Revista Indexada
    URI: 
    https://reunir.unir.net/handle/123456789/11201
    DOI: 
    http://dx.doi.org/10.1142/S0218488520400115
    Dirección web: 
    https://www.worldscientific.com/doi/abs/10.1142/S0218488520400115
    Resumen:
    Monte-Carlo methods are the basis for solving many computational problems using repeated random sampling in scenarios that may have a deterministic but very complex solution from a computational point of view. In recent years, researchers are using the same idea to solve many problems through the so-called Monte-Carlo Tree Search family of algorithms, which provide the possibility of storing and reusing previously calculated results to improve precision in the calculation of future outcomes. However, developers and researchers working in this area tend to have to carry out software developments from scratch to use their designs or improve designs previously created by other researchers. This makes it difficult to see improvements in current algorithms as it takes a lot of hard work. This work presents JGraphs, a toolset implemented in the Java programming language that will allow researchers to avoid having to reinvent the wheel when working with Monte-Carlo Tree Search. In addition, it will allow testing experiments carried out by others in a simple way, reusing previous knowledge.
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