Autonomy and Machine Intelligence in Complex Systems: A Tutorial

Abstract

This tutorial paper will discuss the development of novel state-of-the-art control approaches and theory for complex systems based on machine intelligence in order to enable full autonomy. Given the presence of modeling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of teams of complex systems, there is a need for approaches that respond to situations not programmed or anticipated in design. Unfortunately, existing schemes for complex systems do not take into account recent advances of machine intelligence. We shall discuss on how to be inspired by the human brain and combine interdisciplinary ideas from different fields, i.e. computational intelligence, game theory, control theory, and information theory to develop new self-configuring algorithms for decision and control given the unavailability of model, the presence of enemy components and the possibility of network attacks. Due to the adaptive nature of the algorithms, the complex systems will be capable of breaking or splitting into parts that are themselves autonomous and resilient. The algorithms discussed will be characterized by strong abilities of learning and adaptivity. As a result, the complex systems will be fully autonomous, and tolerant to communication failures.

Meeting Name

American Control Conference (ACC) (2015: Jul. 1-3, Chicago, IL)

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Algorithms; Artificial Intelligence; Complex Networks; Computation Theory; Decision Theory; Embedded Systems; Game Theory; Information Theory; Large Scale Systems; Network Security; Networks (circuits); Uncertainty Analysis; Autonomy; Communication Failure; Cyber Physical Systems (CPSs); Machine Intelligence; Malicious Attack; Model Uncertainties; Self-Configuring Algorithm; State of the Art; Control Theory; Complex Systems; Cyber-Physical Systems; Networks

International Standard Book Number (ISBN)

978-1479986842

International Standard Serial Number (ISSN)

0743-1619

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jul 2015

Link to Full Text

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