UBI 622 Multiagent Systems

Spring 2025

Instructor: Prof. Dr. Geylani KARDAŞ (geylani.kardas@ege.edu.tr)

Assistant: TBA

Time: Thursday 13:30 – 16:00 (started at 27.02.2025)

Office Hour: TBA

All important information about the course will be available from this web page.

Announcements:

• (06.03.25) First assignment has been announced!
• (05.03.25) Second week’s slides have been uploaded.
• (11.02.25) IMPORTANT NOTICE: There is a prerequisite to select this course: Candidate students should successfully complete the course “0301537 Agent-oriented Software Development” prior to registering this course. Candidate students should contact the instructor before the registration.

Course Description:

This course mainly covers design and implementation of software agents within the scope of agent-oriented software engineering (AOSE). Topics include: Autonomous agents and multiagent systems (MAS), agent architectures, introduction of IEEE FIPA specifications, communication in MASs, interaction and cooperation in MASs, agent methodologies for MAS development, agents on the semantic web, MAS metamodeling and model driven development of MASs.

Prerequisites:

The course “0301537 Agent-oriented Software Development” must have been successfully completed prior to this course. Further, one or more MAS development projects are planned. Hence, students need to be fluent in Java programming language and have knowledge on the related software design principles since required MAS development tools are mostly based on Java.

Course Material:

• Required: Lecture slides and papers (available on the course’s web page)
• Recommended books:
• Agent-Oriented Software Engineering: Reflections on Architectures, Methodologies, Languages, and Frameworks. Onn Shehory and Arnon Sturm (Eds.), Springer, 2014.
• An Introduction to Multiagent Systems (2nd edition). Michael Wooldridge, John Wiley & Sons, 2009.
• Methodologies and Software Engineering for Agent Systems (The Agent-Oriented Software Engineering Handbook). Federico Bergenti, Marie-Pierre Gleizes and Franco Zambonelli (Eds.), Kluwer Academic Publishers, 2004.
• Agent-oriented Methodologies. Brian Henderson-Sellers and Paolo Giorgini (Eds.), Idea Group Publishing, 2005.
• Developing Multi-Agent Systems with JADE. Fabio L. Bellifemine, Giovanni Caire and Dominic Greenwood, Wiley Publishing Inc., 2007.
• Multi-Agent Oriented Programming: Programming Multi-Agent Systems Using JaCaMo. Olivier Boissier, Rafael H. Bordini, Jomi Hübner and Alessandro Ricci, MIT Press, 2020.
• Development Tools:
• DSML4BDI - A DSML for Multi-agent Systems: http://akademik.ube.ege.edu.tr/serlab/resources.html#DSML4BDI
• JaCaMo Framework: http://jacamo.sourceforge.net/
• JACK Agent-oriented Development Environment: https://www.aosgrp.com/products/jack/
• Java Agent Development Framework (JADE): http://jade.tilab.com/
• JADEX BDI Agent System: https://www.activecomponents.org/#/project/news
• Prometheus Design Tool: https://sites.google.com/site/rmitagents/software/prometheusPDT

Tentative Course Syllabus:

Date	Topics	Assignments
27.02	Course Introduction
06.03	Software Agents	Assignment 01
13.03	Java Agent DEvelopment Framework (JADE) Book Trading Example as a Maven Project Project Website of the Book Trading Example
20.03	AOSE Methodologies
27.03	JaCaMo Framework JaCaMo Installation Guide
03.04	No Class due to Instructor’s Official Duty
10.04	Model Driven Development of Multi-agent Systems
17.04	Exam
24.04	Break for Midterm
01.05	Legal Holiday
08.05	LCDP4BDI: An Online Modeling Language for the Low-code Development of BDI Agents LCDP4BDI User Manual
15.05	Evaluation study on LCDP4BDI (Part 1)
22.05	Evaluation study on LCDP4BDI (Part 2)
29.05	SEA_ML: A Domain-specific Modeling Language for Multi-agent Systems Interoperability between Domain-specific Modeling Languages for Multi-agent Systems Blockchain Applications on Multi-agent Systems
05.06	Legal Holiday
12.06	Development of Autonomous Cyber-physical Systems using Intelligent Agents and Lego Technology Agent-based Digital Twins
19.06	Methodology Research Presentations

Grading (Tentative):

• Homework 30%
• Exam 30%
• Evaluation Studies 40%