Quantum Fuzzy Inference Engine (QFIE)

On the Implementation of Fuzzy Inference Engines
on Quantum Computers

by Giovanni Acampora, Roberto Schiattarella and Autilia Vitiello

Quantum computing is taking an increasingly central role in the efficient design of a variety of algorithms for artificial and computational intelligence. In recent years, different quantum approaches have been developed for machine learning and evolutionary computation, but to date there are no established research activities in the area of the implementation of fuzzy inference engines on actual quantum computers. This paper bridges this gap by introducing an oracle-based quantum algorithm to run fuzzy rules on quantum devices. The oracle-based design approach, already used in some well-known quantum algorithms such as Grover's and Deutsch-Josza's, achieves two remarkable goals: it provides exponential acceleration in the execution of fuzzy rules compared to the classical counterpart, and it enables a quantum computer to be programmed by fuzzy linguistic rules.

Click on this Binder link to run the Jupyter Notebook to perform experiments on controlling the Inverse Pendulum System by using QFIE:

Click on this Binder link to run the Jupyter Notebook to perform experiments on controlling a Lighting System by using QFIE:

Click on this Binder link to run the Jupyter Notebook to perform experiments on controlling a Computer Cooling System by using QFIE:

A Python package for easily use QFIE has been developed and it can be found at:
QFIE package 

Submitted to IEEE Transaction on Fuzzy Systems