IDENTIFYING DATA 2019_20
Subject (*) MULTI-AGENT SYSTEMS Code 17685104
Study programme
Computer Security Engineering and Artificial Intelligence (2016)
 Cycle 2nd
Descriptors Credits Type Year Period
4.5 Compulsory First 1Q
Language
Anglès
Department Computer Engineering and Mathematics
Coordinator
ISERN ALARCÓN, DAVID
 E-mail
Lecturers
Web http://moodle.urv.cat
General description and relevant information Conceptes bàsics de l'àrea dels agents intel·ligents i els sistemes multi-agent.

Competences
Type A Code Competences Specific
 A1 Integrate the fundamental technology, applications, services and systems of Computer Security and Artificial Intelligence,in a broader, multidisciplinary context.
 A5 Analyse the information needs considered in an environment and execute all stages of the construction process of a secure information system.
 A9 Apply computational, mathematical, statistical and artificial intelligence methods in order to model, design and develop applications, services, smart systems and knowledge-based systems.
 G1 Project, calculate and design products, processes and installations in the areas of Computer Security and Artificial Intelligence
 G2 Perform mathematical modelling, calculation and simulation in company technology and engineering centres, particularly in tasks of research, development and innovation in the areas of Computer Security and Artificial Intelligence
Type B Code Competences Transversal
 CT2 Forming opinions on the basis of the efficient management and use of information
 CT3 Solve complex problems critically, creatively and innovatively in multidisciplinary contexts.
 CT4 Work in multidisciplinary teams and in complex contexts.
 CT5 Communicate complex ideas effectively to all sorts of audiences
 CT7 Apply ethical principles and social responsibility as a citizen and a professional.
Type C Code Competences Nuclear

Learning outcomes
Type A Code Learning outcomes
 A1 Analyse the problems and their causes from a global focus in the medium and long term.
Integrate devices and/or computational methods in various contexts.
 A5 Identify the components of a decision-making problem and know how to decide the most suitable decision-making model.
 A9 Differentiate the various types of smart agents and know how to use each of them.
 G1 Integrate theoretical knowledge into the realities to which it may apply.
 G2 Apply the techniques learned in a specific context.
Type B Code Learning outcomes
 CT2 Manage information and knowledge by making efficient use of the information technologies.
 CT3 Recognise the situation as a problem in a multidisciplinary, research or professional environment, and take an active part in finding a solution.
 CT4 Participate in the group in a good working environment and help to solve problems.
 CT5 Produce a persuasive, consistent and precise discourse that can explain complex ideas and effectively interact with the audience.
 CT7 Apply ethical and socially responsible principles as a citizen and a professional.
Type C Code Learning outcomes

Contents
Topic Sub-topic
Intelligent agents (6 hs) Intelligent agents. Definition. Architectures. Properties. Typology.
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 1.5 2.5
Presentations / oral communications
A5
G2
CT2
CT5
 1 1.5 2.5
Debates
A5
G2
CT2
 1 1.5 2.5
Reading written documents and graphs
A9
 25 37.5 62.5
Assignments
A1
G1
CT3
CT4
CT7
 13 19.5 32.5
Personal attention
1 0 1
 
Multiple-choice objective tests
A9
 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.
Presentations / oral communications Presentation of the practical exercise at the end of the term.
Debates Discussions during the term on the practical exercise to be developed.
Reading written documents and graphs Lectura i estudi dels continguts de l’assignatura.
Assignments Realització d’exercicis pràctics usant les TIC i guiades pel professor.
Personal attention Personalised support to clarify the doubts on the theoretical concepts and to solve practical exercises with agent technology.

Personalized attention
Description
Personalised support through ICTs (mail, chat, videoconference) to clarify the doubts on the theoretical concepts and to solve practical exercises with agent technology.

Assessment
Methodologies Competences Description Weight        
Presentations / oral communications
A5
G2
CT2
CT5
 Presentation of the results of the practical exercise. 30%
Assignments
A1
G1
CT3
CT4
CT7
 Realització individual d’exercicis pràctics usant les TIC 50%
Multiple-choice objective tests
A9
 Short test-style questions on the theoretical content of the course. 20%
Others  
 
Other comments and second exam session

The second call will have the same evaluation than the first one.

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
(*)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.