Q-learning and MCTS techniques for improving an algorithm to compute discrete vector fields on finite topological spaces
- Julián Cuevas-Rozo 12
- Jose Divasón 2
- Laureano Lambán 2
- Ana Romero 2
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1
Universidad Nacional de Colombia
info
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2
Universidad de La Rioja
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- Temur Kutsia (ed. lit.)
Editorial: RISC Report Series
ISSN: 2791-4267
Año de publicación: 2021
Páginas: 6-10
Congreso: 9th International Symposium on Symbolic Computation in Software Science (SCSS 2021)
Tipo: Aportación congreso
Resumen
In this work we present an ongoing project on the improving of a previous symboliccomputation algorithm computing discrete vector fields on finite topological spaces. To this aim, we consider different strategies to choose each one of the possible vectors at each step of the algorithm and we apply some reinforcement learning techniques.