Introduction

Autonomous Learning Systems: From Data Streams to Knowledge in Real Time

by Plamen Angelov

Lecture 1

ALS by P Angelov (c) 2013 Wiley LN1 Intro

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Intro to ALS These lecture notes accompany the book on ALS They can be used with the book and the software

for courses on ALS and related subjects of:

Machine learning (ML); System engineering (specifically, system

identification), SI; Data mining, DM; Statistical Analysis, SA; Pattern Recognition including clustering,

classification, PR; Fuzzy logic and fuzzy systems, including neuro-

fuzzy systems, FL;

ALS by P Angelov (c) 2013 Wiley LN1 Intro

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Outline of the ALS course 20-30h lectures 20 h practical session using the EST software

Lectures cover: Introduction to ALS (1h) Probability theory-basics (2h) Machine Learning & Pattern recognition (2h) Fuzzy Systems Theory – basics (2h) Evolving System Structure (2h) Parameters Learning (1h) Autonomous Predictors/Estimators/Filters/

Inferential Sensors (1h)…

ALS by P Angelov (c) 2013 Wiley LN1 Intro

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Outline of the ALS course … … AL Classifiers (1h) AL Controllers (1h) Collaborative ALS (1h) AL Sensors in (Petro-) Chemical industry (1h) ALS in Mobile Robotics (1h) Autonomous Novelty Detection (1h) Modelling Evolving user behaviour with ALS (1h) Review (1h) Tutorial (1h)

ALS by P Angelov (c) 2013 Wiley LN1 Intro

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Outline of Lecture1 Introduction to ALS Autonomous Systems (AS) The role of Machine Learning (ML) in AS System Identification – A World Model

System structure identification Parameter identification Novelty detection, outliers, structure identification

Online vs Offline Adaptive and Evolving Evolving vs Evolutionary Supervised vs unsupervised learning

ALS by P Angelov (c) 2013 Wiley LN1 Intro

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Introduction to ALS

ALS interacts with a number of well established areas of research ( a non exhaustive list is shown below):

ML

SI

DM

SA

PR

FL

ALS