Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...

The TensorDL-MPC toolbox is a Python-based software developed using the TensorFlow framework. It leverages deep learning techniques to enhance the performance of traditional Model Predictive Control ...

A new machine learning approach that draws inspiration from the way the human brain seems to model and learn about the world has proven capable of mastering a number of simple video games with ...

Lucas is a writer and narrative designer from Argentina with over 15 years of experience writing for games and news. He keeps a watchful eye at the gaming world and loves to write about the hottest ...

Abstract: The Deep Q-Network (DQN) has emerged as a robust deep reinforcement learning algorithm capable of learning optimal policies in complex, high-dimensional environments. The Snake game presents ...

Aiming at the problems of slow network convergence, poor reward convergence stability, and low path planning efficiency of traditional deep reinforcement learning algorithms, this paper proposes a ...

The following project concerns the development of an intelligent agent for the famous game produced by Nintendo Super Mario Bros. More in detail: the goal of this project was to design, implement and ...

Abstract: Non-orthogonal Multiple Access (NOMA) is a crucial technique in Cognitive Radio Networks (CRNs) that improves frequency band use efficiency. However, NOMA may encounter difficulties due to ...

what is going on guys welcome back in this video today we're going to learn how to train a reinforcement learning agent in Python using Q learning so let us get right into it not [Music] a all right ...