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Risorse bibliografiche
Risorsa bibliografica obbligatoria
Risorsa bibliografica facoltativa
Scheda Riassuntiva
Anno Accademico 2017/2018
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 089169 - AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS
Docente Amigoni Francesco
Cfu 5.00 Tipo insegnamento Monodisciplinare

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (Mag.)(ord. 270) - MI (473) AUTOMATION AND CONTROL ENGINEERING - INGEGNERIA DELL'AUTOMAZIONE*AZZZZ089169 - AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS
Ing Ind - Inf (Mag.)(ord. 270) - MI (481) COMPUTER SCIENCE AND ENGINEERING - INGEGNERIA INFORMATICA*AZZZZ089169 - AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS

Programma dettagliato e risultati di apprendimento attesi

Aims and learning outcomes

Computer systems are widely recognized to be increasingly distributed and interconnected. This trend naturally leads to the development of systems composed of autonomous decision-making entities, called agents, that interact with each other in complex environments. Agent-based systems can be identified in several applications, including electronic commerce, control of industrial processes, logistics, ambient intelligence, web services, robotics, space systems, and modeling of complex systems. This course aims at presenting general techniques for developing multiagent systems, independently of the applicative domains. In particular, the course will present methods for developing single agents, able to make rational decisions in situations affected by uncertainty, and for developing systems composed of multiple agents, with special emphasis on the interaction between the agents. Moreover, some real-world applications of agent systems will be discussed. At the end of the course, students will acquire the ability to design and develop distributed systems based on the agent paradigm.

 

Syllabus

1. Introduction to the concepts of autonomous agents and of multiagent systems.

2. Autonomous agents as rational decision makers: utility functions, Markov decision processes, optimal policies.

3. Self-interested interactions between agents: short introduction to game theory, negotiations, voting mechanisms, auctions, coalition formation.

4. Cooperative interaction between agents: decision-theoretic multiagent planning, distributed constraint handling.

5. Multiagent learning: distributed Markov decision processes, evolutionary game theory.

6. Real-world applications of agent-based systems.

 

Prerequisites

Basic programming, algebra, mathematical analysis, probabilities, and mathematical programming.

 

Further information

For further information about the course:
http://home.deib.polimi.it/amigoni/AutonomousAgentsAndMultiagentSystems.html


Note Sulla Modalità di valutazione

The students' evaluation is based on a 1.5-hour written exam, consisting in exercises and questions.


Bibliografia
Risorsa bibliografica obbligatoriaGerhard Weiss (editor), Multiagent Systems (second edition), Editore: The MIT Press, Anno edizione: 2013, ISBN: 978-0-262-01889-0 http://www.the-mas-book.info
Risorsa bibliografica facoltativaFurther teaching material could be possibly made available along the course.

Mix Forme Didattiche
Tipo Forma Didattica Ore didattiche
lezione
32.0
esercitazione
16.0
laboratorio informatico
0.0
laboratorio sperimentale
0.0
progetto
0.0
laboratorio di progetto
0.0

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
schedaincarico v. 1.6.1 / 1.6.1
Area Servizi ICT
28/02/2020