In:
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, World Scientific Pub Co Pte Ltd, Vol. 28, No. Supp02 ( 2020-12), p. 1-22
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
0218-4885
,
1793-6411
DOI:
10.1142/S0218488520400115
Language:
English
Publisher:
World Scientific Pub Co Pte Ltd
Publication Date:
2020
SSG:
24,1
SSG:
17,1
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