Quantum Robotics, Neural Networks and the Quantum Force Interpretation

51 Pages Posted: 24 Sep 2018

Date Written: September 5, 2018


A future quantum technological infrastructure demands the development of quantum cyber-physical-cognitive systems, merging quantum artificial intelligence, quantum robotics and quantum information and communication technologies. To support such a development, the current work introduces a new interpretation of quantum mechanics, grounded on a link between quantum computer science, systems science and field-based computation. This new interpretation is applied to quantum artificial neural networks, with examples implemented experimentally on IBM's five qubit transmon bowtie chip, accessed via cloud using IBM Q Experience, illustrating how quantum neural computing can be implemented on actual quantum computers. A new form of quantum neural machine learning, based on a quantum optimization of a conditional utility function is also introduced and applied to quantum robotics, where a quantum robot, characterized by an interface and a multilayer quantum artificial neural network, interacts with a quantum target, changing the target's dynamics adaptively, based upon the quantum optimization dynamics, computing the optima for a performance measure and changing the target's dynamics accordingly.

Keywords: Quantum Robotics, Quantum Neural Machine Learning, Quantum Force Interpretation, Quantum Optimization

Suggested Citation

Gonçalves, Carlos Pedro dos Santos, Quantum Robotics, Neural Networks and the Quantum Force Interpretation (September 5, 2018). Available at SSRN: https://ssrn.com/abstract=3244327 or http://dx.doi.org/10.2139/ssrn.3244327

Carlos Pedro dos Santos Gonçalves (Contact Author)

Political and Strategic Studies Institute (ISCSP-IEPE) ( email )

Pólo Universitário do Alto da Ajuda
Rua Almerindo Lessa
Lisbon - Lisboa, 1349-055

HOME PAGE: http://sites.google.com/site/carlospedrogoncalves/

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