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MULTIAGENTS SYSTEMS

CODE 90545
ACADEMIC YEAR 2021/2022
CREDITS 6 credits during the 2nd year of 10852 COMPUTER SCIENCE (LM-18) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR INF/01
LANGUAGE English
TEACHING LOCATION GENOVA (COMPUTER SCIENCE )
SEMESTER 1° Semester
TEACHING MATERIALS AULAWEB

OVERVIEW

Multiagent systems (MASs) have emerged as one of the most important areas of research and development in information technology. A MAS is composed of multiple interacting software components (agents) capable of cooperating to solve problems that are beyond the abilities of any individual member.

This course will introduce the students to the notion of an agent, and will lead them to understanding what an agent is, how they can be constructed, how agents can be made to cooperate effectively.

AIMS AND CONTENT

LEARNING OUTCOMES

Getting acquainted with the concept of an agent and multiagent system, and learning how to design intelligent autonomous agents and how to deal with the main implementation issues.

AIMS AND LEARNING OUTCOMES

Upon completing this course, a student will:
-- understand the notion of an agent, how agents are distinct from other software paradigms (e.g., objects), and understand the characteristics of applications that lend themselves to an agent-oriented solution;
-- understand the key issues associated with constructing agents capable of intelligent autonomous action, and the main approaches taken to developing such agents;
-- understand the key issues and approaches to high-level communication in multiagent systems;
-- understand the main application areas of agent-based solutions.

TEACHING METHODS

Traditional: frontal lessons and laboratories

SYLLABUS/CONTENT

Introduction to agents and MASs
-- What is an agent, what is a MAS
-- History of agents and MASs
-- Agent-oriented software engineering

Communication as action
-- Foundations of the speech acts theory
-- Issues in communication
            
Agent-oriented programming (AOP): the foundations              
-- Jason
            
Agent-based modeling and simulation
-- NetLogo

MAS infrastructures         
-- JADE

Distributed AI: some classical issues 
-- Uninformed search
-- Informed search
-- Planning

RECOMMENDED READING/BIBLIOGRAPHY

The slides and the teaching material provided during the course is enough for following it

TEACHERS AND EXAM BOARD

Exam Board

VIVIANA MASCARDI (President)

FILIPPO RICCA

GIORGIO DELZANNO (President Substitute)

LESSONS

TEACHING METHODS

Traditional: frontal lessons and laboratories

Class schedule

All class schedules are posted on the EasyAcademy portal.

EXAMS

EXAM DESCRIPTION

The exam will consist in a quiz, a written part (traditional open/closed questions, exercises) plus an individual project (requiring about 1 man/week to be completed).

ASSESSMENT METHODS

The acquisition of the skills foreseen by this course are assessed via the quiz + written exam + the project which have been carefully designed to allow the teacher to verify whether a student is actually able to:
-- understand the notion of an agent, how agents are distinct from other software paradigms (e.g., objects), and understand the characteristics of applications that lend themselves to an agent-oriented solution;
-- understand the key issues associated with constructing agents capable of intelligent autonomous action, and the main approaches taken to developing such agents;
-- understand the key issues and approaches to high-level communication in multiagent systems;
-- understand the main application areas of agent-based solutions.

Exam schedule

Date Time Location Type Notes
22/07/2022 09:00 GENOVA Esame su appuntamento
16/09/2022 09:00 GENOVA Esame su appuntamento
10/02/2023 09:00 GENOVA Esame su appuntamento