Trabalho de Conclusão de Curso de Graduação
Modelagem matemática e desenvolvimento de um agente baseado em modelos Markovianos
Fecha
2020-09-30Autor
Rossato, Lana Bertoldo
Institución
Resumen
In the last years, it is possible to see the advance of Artificial Intelligence applied to the
most diverse games, whether they are deterministic or stochastic. Many techniques, despite
achieving the expected result, require considerable computational power and are not
viable on more basic platforms (e.g., low-cost smartphones). Thus, there is a need to create
light weight techniques. This work uses Markov Chains in the development of an agent
for a card game. The modeling was performed to represent the natural order of the forces
and separates it into three modules according to the game’s modalities, being: Truco,
Envido and Flor. Decision making is based on games played previously, reinforcing the
decisions made and improving them. To evaluate the model, several rounds of tests were
made, varying the opponent and the databases. This process resulted in learning matrices
for each game mode. Thus, they were evaluated considering the main characteristics of the
model and also of the opponents.