The rise of Artificial Intelligence (AI) enables enterprises to manage large amounts of data in order to derive data-driven predictions about future performance and to gain meaningful insights. In this context, descriptive and predictive analytics has gained a significant research attention.
The proposed approach of Human-Augmented Prescriptive Analytics With Interactive Multi-Objective Reinforcement Learning has been deployed in a stock market case study in order to evaluate the proactive trading decisions that will lead to the maximum return and the minimum risk that the user experience and the available data can yield in combination.
Katerina Lepenioti; Alexandros Bousdekis; Dimitris Apostolou; Gregoris Mentzas
(July 12th 2021)