TCC - Bacharelado em Sistemas da Informação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/427
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Resultados da Pesquisa
Item Otimização de equipes em League of Legends utilizando algoritmos genéticos multiobjetivo(2022-06-03) Vieira, Lucas Marsol; Garrozi, Cícero; http://lattes.cnpq.br/0488054917286587League of Legends, a game of the Multiplayer Online Battle Arena or MOBA category (as it is popularly known), continues to be one of the highest paying electronic games in the world. This category is based on two teams that face each other on a symmetrical map with the objective of destroying the opposing base. One of the main points in this style of play and more specifically in League of Legends is the character selection stage (also known as champions), as it will guide the strategy of each team. In this step, players select which characters they will use within the game, where each character has characteristics and abilities that are different from the others. As it involves several factors in the selection process, it is considered a complex problem that can be solved with search techniques and artificial intelligence to find the best solutions. In this project, a new approach through Multi-Objective Evolutionary Algorithms (MOEA) is presented to generate teams in the game. In order to estimate the quality of the generated teams, a survey was conducted with a group of players. Significant results were achieved with this approach, obtaining an average rating of 4.5 for a total of 5 points.Item Um algoritmo para geração de Navigation Meshes em mapas bidimensionais homogêneos: uma aplicação no jogo Dragon Age: Origins(2019) Costa, Ingrid Danielle Vilela; Bocanegra, Silvana; http://lattes.cnpq.br/4596111202208863; http://lattes.cnpq.br/6113606913639280In the field of electronic gaming and more recently in robotics, autonomous agent soften need to repeatedly solve the problem of searching for the smallest path. This need can eventually consume a lot of resources and demands optimizations to make these searches more efficient. Such optimizations may include improvements in search algorithms, map representation, data structures used. This work presents an optimization for search algorithms based on the reduction of the search space by means of an automatic Navigation Meshes generation algorithm which are networks of walka blemap areas implying in a reduction of the search space and consequently improving the search processing time. The generation of Navigation Meshes is a problem with no consolidated solution. To prove the heuristic, path finding problems were solved on 156 benchmark maps. The path findings were performmed by the A* algorithm and the solutions were compared between the original maps and the optimized ones. An average search space reduction of 97.42% was achieved, with a standard deviation of 0.026and the search had an average marginal reduction in execution time of 46.76%.