Multiagent Systems

The main objective of this course is to learn to distinguish the appropriate problems for the development of multiagent systems, as well as their main characteristics. The concept of intelligent agent will be introduced and the main
theories and models will be detailed, as well as the different architectures of multi-agent systems and their most
relevant applications.

Agents and agent architectures. Interaction needs between agents: negotiation,
cooperation, coordination. Agent-oriented methodologies.

Basic:
M. Wooldridge (2009). An introduction to multiagent systems. John Wiley and Sons, 2 Edition, ISBN 978-
0470519462
Complementary:
G. Weiss (1999). Multiagent systems: A modern approach to distributed artificial intelligence. MIT Press, ISBN
978-0262731317

BASIC AND GENERAL
GC1 - Maintain and extend theoretical approaches founded to allow the introduction and exploitation of new and
advanced technologies in the field of Artificial Intelligence.
CG3 - Search and select useful information needed to solve complex problems, handling with fluency the
bibliographic sources of the field.
CB6 - Possess and understand knowledge that provides a basis or opportunity to be original in the development
and/or application of ideas, often in a research context.
CB7 - That students know how to apply the acquired knowledge and problem-solving skills in new or unfamiliar
environments within broader (or multidisciplinary) contexts related to their area of study.
CB8 - That students are able to integrate knowledge and face the complexity of making judgments based on
information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to
the application of their knowledge and judgments.
TRANSVERSALS
CT2 - Master the oral and written expression and comprehension of a foreign language.
CT3 - Use the basic tools of information and communication technologies (ICT) necessary for the exercise of their
profession and for lifelong learning.
CT4 - Develop for the exercise of a citizenship respectful of democratic culture, human rights and gender perspective.
CT6 - Acquire life skills and healthy habits, routines and lifestyles.
CT8 - Value the importance of research, innovation and technological development in the socioeconomic and cultural
advancement of society.
SPECIFIC
CE5 - Ability to design and develop intelligent systems through the application of inference algorithms, knowledge
representation and automatic planning.
SC6 - Ability to recognize those problems that need a distributed architecture that is not prefixed during the system
design, which will be suitable for the implementation of intelligent multi-agent systems.
SC7 - Ability to understand the implications of the development of an explainable and interpretable intelligent
system.
CE8 - Ability to design and develop secure intelligent systems, in terms of integrity, confidentiality and robustness.

The methodology includes the expository method / lecture, laboratory practices, tutorials, independent work, case
studies, project-based learning. It will be carried out with the following training activities:
1) Problem-based learning, seminars, case studies and projects: these are sessions whose objective is that students
acquire certain skills based on the resolution of exercises, case studies and projects that require the student to apply
the knowledge and skills developed during the course. These sessions may require the student to present orally the
solution to the problems posed. The work carried out by the students can be done individually or in work groups.
2) Theory classes: Oral exposition complemented with the use of audiovisual media and the introduction of some
questions directed to the students, with the purpose of transmitting knowledge and facilitating learning. In addition to
the time of oral exposition by the professor, this formative activity requires the student to dedicate some time to
prepare and review on their own the materials object of the class.
3) Practical laboratory classes: classes dedicated to the development of practical work involving the resolution of
complex problems, and the analysis and design of solutions that constitute a means for their resolution. This activity
may require students to present their work orally. The work done by the students can be done individually or in work
groups.
Sistema

The assessment will consist of two parts:

- Final exam, with weighting of 40% of the final grade.

- Evaluation of practical work, with a weighting of 60% of the final grade.

It will be necessary to reach 40% of the score in each part in order to pass the subject.

The grade will be not presented when no practical work or final exam is handed in.

Second opportunity

The evaluation will be carried out with the same criteria described above. A new term will be opened for the delivery of the practical work, in case of not having delivered them in the first opportunity.

A1: Theory classes: 21 classroom hours, 42 hours total dedication.
A2: Practical laboratory classes: 14 classroom hours, 40 hours total dedication.
A3: Problem-based learning, seminars, case studies and projects: 7 classroom hours, 68 hours total dedication