Scripted AI for Overcooked

Abstract

Overcooked, an immersive multiplayer video game centered around cooperative cooking challenges, provides the roots for this research project. The study focuses on designing and evaluating a hand-authored controller in comparison to controllers implemented using various machine learning techniques, such as Population Based Training, in the context of a simplified version of the game. The main objective is to assess the cooperation between the hand-authored controller and a human controlled agent, with a particular emphasis on the coordination and minimizing errors during runs of fixed time length. A testing method has been designed in order to more accurately evaluate the performance. Through the implementation of a specialized controller utilizing techniques such as Behavior Trees and Decision Trees, the controller was able to successfully accomplish the task of delivering soups. An analysis was made to examine the performance of the hand-authored controller in comparison to the results obtained in other research papers that use the same simplified version of the game. After the results have been obtained, a clear difference was visible. The scripted AI performed better when paired with himself than one created with population based training that was paired with himself. However, the scripted AI was not better than a coupled planning algorithm that was paired with himself, but the computations were easier and faster for the scripted AI. When paired with a human, the overall performance decreases, but increases only for one specific map.