modules

This module explores the artificial intelligence paradigm and its capacity for developing smarter automation and control systems. Through practical examples, and underpinned by rigorous theory, you will develop an understanding of the key objectives of intelligent agents, namely to correctly interpret data from observations of their environment, to learn from data, and to carry out tasks and complete goals by responding to the learning. Key to this process are feedback loops between the agent and its environment. Control theory is the science of feedback mechanisms and as such underpins the AI paradigm.

Many current developments in the field of artificial intelligence combine data analysis, machine learning and control engineering approaches and so enable intelligent agents to complete complex tasks. In this module you will develop skills in signal processing, reinforcement/adaptive learning, dynamical systems and control, and apply these to design intelligent agents in relevant application areas such as autonomous vehicles, communication and information systems, and smart grid technologies.

_{Please note that all modules are subject to change, please get in touch if you have any questions about this module.}