A Survey of Brain Inspired Technologies for Engineering

TL;DR

This survey reviews diverse brain-inspired technologies in cognitive engineering, highlighting their approaches, strengths, weaknesses, and potential for integration to advance the development of cognitive machines.

Contribution

It provides a holistic overview of various brain-inspired methods, clarifies their differences, and explores how they can be combined to improve cognitive machine development.

Findings

Different approaches have unique strengths and weaknesses.

Potential for integrating diverse methods to create better cognitive machines.

Highlights the need for unified frameworks in cognitive engineering.

Abstract

Cognitive engineering is a multi-disciplinary field and hence it is difficult to find a review article consolidating the leading developments in the field. The in-credible pace at which technology is advancing pushes the boundaries of what is achievable in cognitive engineering. There are also differing approaches to cognitive engineering brought about from the multi-disciplinary nature of the field and the vastness of possible applications. Thus research communities require more frequent reviews to keep up to date with the latest trends. In this paper we shall dis-cuss some of the approaches to cognitive engineering holistically to clarify the reasoning behind the different approaches and to highlight their strengths and weaknesses. We shall then show how developments from seemingly disjointed views could be integrated to achieve the same goal of creating cognitive machines. By reviewing the major contributions in the different fields and showing the potential for a combined approach, this work intends to assist the research community in devising more unified methods and techniques for developing cognitive machines.