Towards Regulated Deep Learning

12/31/2019
by   Andrés García-Camino, et al.
0

Regulation of Multi-Agent Systems (MAS) was a research topic of the past decade and one of these proposals was Electronic Institutions. However, with the recent reformulation of Artificial Neural Networks (ANN) as Deep Learning (DL), Security, Privacy, Ethical and Legal issues regarding the use of DL has raised concerns in the Artificial Intelligence (AI) Community. Now that the Regulation of MAS is almost correctly addressed, we propose the Regulation of ANN as Agent-based Training of a special type of regulated ANN that we call Institutional Neural Network. This paper introduces the former concept and provides I, a language previously used to model and extend Electronic Institutions, as a means to implement and regulate DL.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/30/2016

Machine Learning for Dental Image Analysis

In order to study the application of artificial intelligence (AI) to den...
research
02/27/2012

On an Ethical Use of Neural Networks: A Case Study on a North Indian Raga

The paper gives an artificial neural network (ANN) approach to time seri...
research
08/04/2020

A non-discriminatory approach to ethical deep learning

Artificial neural networks perform state-of-the-art in an ever-growing n...
research
04/08/2019

Modelling PM10 Crisis Peaks Using Multi-Agent based Simulation: Application to Annaba City, North-East Algeria

The paper describes a MAS (multi-agent system) simulation approach for c...
research
10/01/2021

Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration

Deep learning has powered recent successes of artificial intelligence (A...
research
07/20/2023

Dense Sample Deep Learning

Deep Learning (DL) , a variant of the neural network algorithms original...
research
10/03/2022

Green Learning: Introduction, Examples and Outlook

Rapid advances in artificial intelligence (AI) in the last decade have l...

Please sign up or login with your details

Forgot password? Click here to reset