Deep Reinforcement Learning in Practice
Research Engineer, InstaDeep and Guest researcher, Max-Planck-Institute
Dr. Nima Siboni, machine learning team lead at DeepMetis, has set his focus on reinforcement learning projects. After finishing his Ph.D. in simulation sciences, he complemented his skills with machine learning techniques, and since then works as an AI/RL practitioner and researcher. His expertise lies at the intersection of AI and simulation, namely optimization, reinforcement learning, and simultelligence.
Unlike the un/supervised learning, which are extensively used in industry, RL is still not that often utilized, in spite of its potential. Nevertheless, there are recent developments in making RL easier to train and more reliable to use. In this workshop, we first examine for which problems RL is a suitable framework, and then we address a minimal but easily extendable use case that could serve as a blueprint for your business problem.