A Minimal Architecture for General Cognition

07/31/2015
by   Michael S. Gashler, et al.
0

A minimalistic cognitive architecture called MANIC is presented. The MANIC architecture requires only three function approximating models, and one state machine. Even with so few major components, it is theoretically sufficient to achieve functional equivalence with all other cognitive architectures, and can be practically trained. Instead of seeking to transfer architectural inspiration from biology into artificial intelligence, MANIC seeks to minimize novelty and follow the most well-established constructs that have evolved within various sub-fields of data science. From this perspective, MANIC offers an alternate approach to a long-standing objective of artificial intelligence. This paper provides a theoretical analysis of the MANIC architecture.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/13/2013

Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (1995)

This is the Proceedings of the Eleventh Conference on Uncertainty in Art...
research
12/12/2018

Designing Artificial Cognitive Architectures: Brain Inspired or Biologically Inspired?

Artificial Neural Networks (ANNs) were devised as a tool for Artificial ...
research
09/06/2019

Agora: Towards An Open Ecosystem for Democratizing Data Science Artificial Intelligence

Data science and artificial intelligence are driven by a plethora of div...
research
01/30/2022

Computational Metacognition

Computational metacognition represents a cognitive systems perspective o...
research
06/23/2023

Thoughts on Architecture

The term architecture has evolved considerably from its original Greek r...
research
09/29/2020

Towards decolonising computational sciences

This article sets out our perspective on how to begin the journey of dec...

Please sign up or login with your details

Forgot password? Click here to reset