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neoPREDiCOM

New Model-Based Multi-Objective Reinforcement Learning Method. Application to Predictive Control

Field
National
Date
01/09/2021 - 31/08/2024
Industry
  • Industry
Budget
Funded by

R&D&I 2020 PROJECTS. RESEARCH CHALLENGES. Ministry of Science, Innovation

Video

PROJECT INFORMATION

DESCRIPTION

The objective of this project is to integrate some AI techniques (such as those based on neural networks, evolutionary computation and reinforcement learning), with advanced control algorithms (such as predictive control), to develop a control architecture capable of being easily integrated into industrial control equipment commonly used in process control.

The objective of this project is to integrate some AI techniques (such as those based on neural networks, evolutionary computation and reinforcement learning), with advanced control algorithms (such as predictive control), to develop a control architecture capable of being easily integrated into industrial control equipment commonly used in process control.

Contact information

Sanchís Saez, Javier
University Professor - PDI

Ai2

Technological capabilities

IA
Predictive and prescriptive analytical technologies