SeLIE’21 – The first International Workshop on

Self-Learning in Intelligent Environments

24 June 2021, Dubai, United Arab Emirates

Aims and Scope

Aims and scope

Self-learning systems are artificial agents able to acquire and renew knowledge over the time by themselves, without any hard coding. These are adaptive systems whose functions improve by a learning process based -typically- on the method of trial and error. A self-learning system interacts with its users or surrounding environment initially by attempts and observes the changes produced by its actions.
This workshop will focus on the design, implementation and exploitation of self-learning features either within an Intelligent Environment as a whole, or within some of its components. The workshop will represent an opportunity for both the academia and industry to debate the state-of-the-art, challenges and open issues.

Topics of interest

  • Self-Learning methods:
    • Reinforcement Learning and Inverse Reinforcement Learning
    • Imitation Learning
    • Learning-by-Demonstration
    • Constructivism approaches
  • Technical issues
    • Environment modeling
    • Partially observable environments
    • Reward engineering
    • Exploitation VS Exploration trade-off
    • Hyperparameters optimization
    • Multi-Agent Reinforcement Learning
    • Hierarchical Reinforcement Learning
  • Self-Learning application fields:
    • Automotive
    • Robotics
    • Healthcare
    • Finance
    • Gaming
    • Business management
    • Resource management
    • Internet of Things


General Chairs:

Antonio Coronato

CNR-ICAR (Italy)

Giovanna Di Marzo Serugendo

University of Geneva (Switzerland)

Programme Chairs:

Mohamed Bakhouya

International University of Rabat (Marocco)

Ayşegül Uçar

Firat University Elazig (Turkey)

Program Committee:

Vincenzo De Florio

Vrije Universiteit Brussel (Belgium)

Claudia Di Napoli

CNR-ICAR (Italy)

Marie-Pierre Gleizes

University Paul Sabatier (France)

Salima Hassas

University Claude Bernard (France)

Jose Luis Fernandez-Marquez

University of Geneva, (Switzerland)

Georgios Meditskos

CERTH, (Greece)

Muddasar Naeem

University La Parthenope (Italy)

Giovanni Paragliola

CNR-ICAR (Italy)

WWW & Social Media Chair:

Angelo Esposito

CNR-ICAR (Italy)

Important Dates

  • Submission Deadline: 1st March 202115th March 2021
  • Notification to Authors: 5th April 2021
  • Camera Ready Deadline: 15 April 2021
  • Workshop dates: Jun 21 - Jun 24 2021


Authors wishing to participate in this event should format their papers according to the IOS Press style, with a length of at least 6 but no more than 10 pages. ​Latex and Word templates can be found in

Submission page:

All papers accepted in the Workshop's program will be published as a volume of the Ambient Intelligence and Smart Environments Series of IOS Press and electronically available through ACM Digital Library (pending approval). Both proceedings will be ISI indexed.

Best paper award

The best paper will be awarded a certificate and a prize of 250 Euros

Special Issues

An extended version of selected papers will be considered for publishing as a contribution of:
1) the Special Issue on Self-Learning Systems and Pattern Recognition and Exploitation of Pattern Recognition Letters
2) the Research Topic on Self-Learning Systems in Frontiers of AI .


The workshop will be co-located with the 17th International Conference on Intelligent Environments (IE2021) Middlesex University Dubai, Dubai, United Arab Emirates.



Monday, 21st of June, 2021

[14:10 – 14:15]

[14:15 – 14:30]
Learning to move an object by the humanoid robots by using deep reinforcement learning Simge Nur ASLAN, Burak TAŞÇI, Ayşegül UÇAR, and Cüneyt GÜZELİŞ

[14:30 – 14:45]
A Self-Learning Autonomous and Intelligent System for the Reduction of Medication Errors in Home Treatments Rosamaria DONNICI, Antonio CORONATO, and Muddasar NAEEM

[14:45 – 15:00]
Self Learning of News Category using AI Techniques Zara HAYAT, Aqsa RAHIM, Sajid BASHIR, and Muddasar NAEEM

[15:00 – 15:30]

[15:30 – 15:45]
An RL-based approach for IEQ optimization in reorganizing interior spaces for home-working Patrizia RIBINO, and Marina BONOMOLO

[15:45 – 16:00]
Inverse Reinforcement Learning through Max-Margin Algorithm Syed Ihtesham Hussain Shah and Antonio Coronato

[16:00 – 16:15]
An overview of Inverse Reinforcement Learning Techniques Syed Ihtesham Hussain Shah and Giuseppe De Pietro

[16:15 – 16:30]
Prediction of Breast Cancer using AI-based Methods Sanam AAMIR, Aqsa RAHIM, Sajid BASHIR and Muddasar NAEEM

[16:30 – 16:40]

Program Download