Abstract: We aim at creating a transfer reinforcement learning framework that allows the design of learning controllers to leverage prior knowledge extracted from previously learned tasks and previous ...

MPC, a well-known control methodology that exploits a prediction model to predict the future behaviour of the environment and compute the optimal action and RL, a Machine Learning paradigm that showed ...

Abstract: Deep reinforcement learning (DRL) and deep multiagent reinforcement learning (MARL) have achieved significant success across a wide range of domains, including game artificial intelligence ...

PenGym is a framework for creating and managing realistic environments used for the training of Reinforcement Learning (RL) agents for penetration testing purposes. PenGym uses the same API with the ...

Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...