A Quantum Production Model

TL;DR

This paper introduces a quantum production system model that integrates quantum computation principles with artificial intelligence problem-solving methods, demonstrating potential speedups using Grover's algorithm.

Contribution

It develops a reversible quantum production system model and shows how it can be combined with Grover's algorithm for faster problem solving.

Findings

Quantum production system modeled as reversible system

Integration with Grover's algorithm yields speedup

Comparison with classical hierarchical search

Abstract

The production system is a theoretical model of computation relevant to the artificial intelligence field allowing for problem solving procedures such as hierarchical tree search. In this work we explore some of the connections between artificial intelligence and quantum computation by presenting a model for a quantum production system. Our approach focuses on initially developing a model for a reversible production system which is a simple mapping of Bennett's reversible Turing machine. We then expand on this result in order to accommodate for the requirements of quantum computation. We present the details of how our proposition can be used alongside Grover's algorithm in order to yield a speedup comparatively to its classical counterpart. We discuss the requirements associated with such a speedup and how it compares against a similar quantum hierarchical search approach.