Intelligent Agent Navigation using Quantum Sparse Distributed Memory Model (QuSDM)

Abstract

Providing human like storage and retrieval mechanism in agency, the proposed agent navigation system is employing a hybrid approach with the ability to address the content classically and to store the data at superposition state. However, the proposed agent navigation system preserves the basic properties of the Sparse distributed memory that makes it practically an acceptable approach to improve an agent navigation while preserving the basic principles of original Sparse distributed memory model. The psychological literature and the neuroscience has revealed the fact that the human mind is a comprehensive memory system instead of a computational device that works in a hyper-dimension at a time. Researchers are continuously trying to improve the working of the advocated pattern storage and retrieval sequences instead of exploring the other domains that have the capacity to provide better results dramatically due to the properties of that domain. Quantum sparse distributed memory model is proposed based on the basic properties of quantum mechanics that has the capacity to provide more human-like storage and retrieval mechanism. Based on the working of the QuSDM model, an intelligent agent navigation system has been proposed. The proposed agent navigation system utilizes the properties of quantum mechanics that results into more intelligent storage and retrieval mechanism. This proposed system works in a hybrid mode with an aptitude to work with our current artificial intelligence tools. The proposed agent navigation system is an attractive system for the navigation due to its hybrid approach with the workability of our current machines in nature.