The goal of the project was to create a new algorithm for Object Detection. The starting point of the project was exposed in "Active Object Localization with Deep Reinforcement Learning", where they described an OD algorithm based on Deep Reinforcement Learning and Markov Decision Process. Since every action taken by the Agent, the algorithm compares the current state with the environment, it takes a long time for the computations, because every state is encoded through a CNN, which is a Neural Network with over 58 million parameters (VGG16-like). The purpose of this project was to design a Model-Based algorithm to bypass the CNN.