IDENTIFYING DATA 2014_15
Subject (*) MULTI-AGENT SYSTEMS Code 17615116
Study programme
Computer security and intelligent systems (2010)
 Cycle 2nd
Descriptors Credits Type Year Period
4.5 Compulsory First 1Q
Language
Anglès
Department Enginyeria Informàtica i Matemàtiques
Coordinator
MORENO RIBAS, ANTONIO
 E-mail jordi.pujol@urv.cat
antonio.moreno@urv.cat
Lecturers
PUJOL AHULLÓ, JORDI
MORENO RIBAS, ANTONIO
Web http://moodle.urv.cat
General description and relevant information Basic concepts in the areas of intelligent agents and multi-agent systems.

Competences
Type A Code Competences Specific
  Research
  AR10 Analitzar, dissenyar i desenvolupar sistemes robotitzats i intel·ligents.
  AR12 Aplicar metodologies de la intel·ligència artificial.
Type B Code Competences Transversal
  Common
  BC4 Resoldre problemes de forma efectiva
  BC5 Transferibilitat. Aplicar coneixements i habilitats en entorns nous o no familiars i en contextos multidisciplinars relatius a la seva àrea específica
  BC6 Actuar amb un esperit crític i responsable.
  BC11 Treballar en equip i gestionar equips
  BC14 Planificació i organització
Type C Code Competences Nuclear
  Common
  CC1 Domini de l’expressió i la comprensió del/s idioma/es estrangers per al desenvolupament professional derivat del curs del postgrau.
  CC2 Ús de les eines específiques de TIC per al desenvolupament professional derivat del curs de postgrau.
  CC4 Desenvolupament d’habilitats informacionals

Learning aims
Objectives Competences
Distinguish different types of intelligent agents and know when to use each of them. AR10
AR12
 BC4
BC5
BC6
BC11
BC14
 CC2
CC4
Obtain information from electronic resources in English CC1
CC2
CC4
Acquire the basic concepts in the theory of agents and multi-agent systems AR10
AR12
 CC1
Collaborate within a team to solve a specific problem using agent technology AR10
AR12
 BC5
BC6
BC11
BC14

Contents
Topic Sub-topic
Intelligent agents (6 hs) Intelligent agents. Definition. Properties. Characteristics. Tipology.
Multi-agent systems (24 hs) Introduction to distributed intelligent systems. Communication. Standards. Coordination. Negotiation. Distributed planning. Voting. Auctions. Coalition formation. Application of MAS to real problems.

Planning
Methodologies  ::  Tests
  Competences (*) Class hours Hours outside the classroom (**) Total hours
Introductory activities
1 0 1
 
Lecture
24 36 60
Practicals using information and communication technologies (ICTs) in computer rooms
15 15 30
Presentations / expositions
1 4 5
Debates
2 4 6
 
Personal tuition
1 0 1
 
Objective short-answer tests
3 6 9
 
(*) On e-learning, hours of virtual attendance of the teacher.
(**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies
  Description
Introductory activities Presentation of the topic, describing the contents, biblography, work mehodology, evaluation mechanism.
Lecture Theoretical exposition by the lecturer of the contents of the course.
Practicals using information and communication technologies (ICTs) in computer rooms Development of practical exercises using ICT, guided by the teacher.
Presentations / expositions Presentation of the practical exercise at the end of the term.
Debates Discussions during the term on the practical exercise to be developed.
Personal tuition Personalised support to clarify the doubts on the theoretical concepts and to solve practical exercises with agent technology.

Personalized attention
 
Introductory activities
Practicals using information and communication technologies (ICTs) in computer rooms
Lecture
Presentations / expositions
Objective short-answer tests
Description
Personalised support to clarify the doubts on the theoretical concepts and to solve practical exercises with agent technology.

Assessment
  Description Weight
Practicals using information and communication technologies (ICTs) in computer rooms Development of team practical exercises using ICT 30%
Presentations / expositions Presentation of the results of the practical exercise 10%
Debates Discussions on the design and implementation of the practical exercise 15%
Objective short-answer tests Questions and exercises on the theoretical contents of the course 45%
 
Other comments and second exam session

L'avaluació en segona convocatòria tindrà els mateixos components que la primera.

Sources of information

Basic A. Mas, Agentes software y sistemas multi-agente, Pearson-Prentice Hall, 2005
M.Wooldridge, An introduction to multiagent systems (2nd ed), Wiley, 2009

Complementary , Info. plana web JADE, ,
, Journal of Autonomous Agents and Multi-Agent Systems, ,
Isern, Sánchez, Guia de programació de sistemes multiagent en JADE 3.3, DEIM-RT-05-001, 2005
G.Weiss, Multiagent Systems. A Modern Approach to Distributed Artificial Intelligence , MIT Press, 1999
M.Fasli, Agent technology for e-commerce , Wiley, 2007

Recommendations

Subjects that are recommended to be taken simultaneously
COOPERATIVE ROBOTICS/17615117

Subjects that it is recommended to have taken before
ARTIFICIAL INTELLIGENCE/17615104
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.