NPC’S: a Fracsland

Abstract

[en] The best way to learn at school is the one which makes you forget that you are studying and allows you to enjoy what you learn. Based on this sentence, this project aims to provide a realistic basis for the videogame through the addition of artificial intelligence techniques, in order to facilitate the mathematical learning of students by making them enjoy a wider and complex gameplay when they interact with the various characters that make up the game. Six different characters have been implemented in two different scenarios of the game, endowed with a set of AI techniques: Steering: A set of techniques that allow to perform the control of the motion of the characters to be implemented based on a single final vector of direction calculated from the influence of the weight of each particular technique on the total. In this way you get the direction that must follow the character who needs to take into account several aspects at the same time, such as the need to escape from a threat without leaving a specific area, for example. State machines: AI technique that allows to perform the control of all the states that form the behavior of the characters. It is a simple but effective technique, since it allows to model the different states belonging to a character with the transitions between these states. Behavior trees: A technique that allows to model complex and precise behaviors through an arboreal structure formed by two types of nodes, intermediate and leaf nodes. The first type is the internal structure of the tree, which allows to define the flow of it, such as the Selector and Sequence nodes, which allows to define a series of actions from which you can choose one at a time (Selector), or define a series of actions that will be executed one after the other until all success or one fails (Sequence). The second type is the leaf nodes, which allows to implement conditions and actions that the characters which possess a tree have to perform. • Shared memory between behavior trees: AI technique that provides a tool to allow the behavior trees of all single-person characters to communicate between them. The goal is to synchronize trees in a more complex and precise way than the group Steering to perform complex group behaviors of humans that form formations, for example.