Print Email Facebook Twitter AI Soccer: the Most Effective Methods to Dispossess the Opponent Player Title AI Soccer: the Most Effective Methods to Dispossess the Opponent Player Author Heslenfeld, Sam (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Intelligent Systems) Contributor Bidarra, Rafael (mentor) Prakash, K. (mentor) Picek, S. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2021-07-01 Abstract In this paper, one of the challenges that comes with defending in AI soccer is highlighted and an attempt is made in finding a solution for the problem. In soccer, defense is an important part of the game and the research question in this research is formulated as follows: what are the most effective methods to take by surprise and dispossess the attacking opponent player who carries the ball? To find the most optimal solutions for this problem, the Webots AI Soccer environment is used, which simulates a game of five versus five soccer. To be able to answer the research question, several approaches and strategies are implemented in the environment and their success is compared. This has led to the conclusion that, in this particular environment, defensive actions like slide tackling cannot be performed and thus cannot be used to defend. Therefore, other solutions are necessary, as a result, a combination of approaches is the most important way of making the dispossession strategy as successful as possible. This combination consists of predicting where the opponent is moving to with the ball and determining the optimal side to approach the opponent from. Subject AISoccerDispossessionWebotsDefense To reference this document use: http://resolver.tudelft.nl/uuid:9feb6511-918d-45b3-b6f7-cecf823e41e8 Part of collection Student theses Document type bachelor thesis Rights © 2021 Sam Heslenfeld Files PDF RP_Paper_Sam_Heslenfeld_N ... _Email.pdf 404.55 KB Close viewer /islandora/object/uuid:9feb6511-918d-45b3-b6f7-cecf823e41e8/datastream/OBJ/view