This library lists the outcomes of our research on video summarization and explainable AI-based summarization.
Application of a Neural Network trained with Reinforcement Learning method aimed to assign production resources to tasks in a production schedule during its execution.
The library includes functionalities to apply reinforcement learning to industrial machines tuning
Traffic Control in a Simulated Environment for Pollution Reduction
Stable Baselines 3 provides open-source implementations of deep reinforcement learning (RL) algorithms in Python.
Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines.
Reinforcement Learning (RL) and State Representation Learning (SRL) Toolbox for Robotics
Nowadays, Artificial Intelligence, notably Advanced Machine Learning (ML) drives scientific and economic growth worldwide. They are essentially massive ‘learning by experience/examples’ systems. However, as our tasks and the world change, such systems sho...
Nowadays, Artificial Intelligence, notably Advanced Machine Learning (ML) drives scientific and economic growth worldwide. They are essentially massive ‘learning by experience/examples’ systems. However, as our tasks and the world change, such systems sho...
In this course, we present formalisms and learning algorithms for non-Markovian decision processes, where rewards and dynamics can depend on the history of events. November 7–21, 2022 (schedule on the web site) Room B203, Department of Computer, Aut...
Coping with the variability of human feedback during interactive learning through ensemble reinforcement learning