Brain-inspired Distributed Cognitive Architecture

TL;DR

This paper introduces a modular, brain-inspired cognitive architecture that models attention and sensory processing, demonstrating efficiency improvements and providing an open-source platform for future AI research.

Contribution

It presents a novel, modular, brain-inspired architecture with attention modeling, implemented as web-servers, and demonstrates bio-inspired processing efficiencies.

Findings

Modeling of high- and low-salience attention modes

Demonstrated processing efficiencies in bio-inspired architecture

Open-source platform for extension and research

Abstract

In this paper we present a brain-inspired cognitive architecture that incorporates sensory processing, classification, contextual prediction, and emotional tagging. The cognitive architecture is implemented as three modular web-servers, meaning that it can be deployed centrally or across a network for servers. The experiments reveal two distinct operations of behaviour, namely high- and low-salience modes of operations, which closely model attention in the brain. In addition to modelling the cortex, we have demonstrated that a bio-inspired architecture introduced processing efficiencies. The software has been published as an open source platform, and can be easily extended by future research teams. This research lays the foundations for bio-realistic attention direction and sensory selection, and we believe that it is a key step towards achieving a bio-realistic artificial intelligent system.