ECTS credits ECTS credits: 3
ECTS Hours Rules/Memories Hours of tutorials: 1 Expository Class: 10 Interactive Classroom: 11 Total: 22
Use languages Spanish, Galician, English
Type: Ordinary subject Master’s Degree RD 1393/2007 - 822/2021
Departments: External department linked to the degrees
Areas: Área externa M.U en Intelixencia Artificial
Center Higher Technical Engineering School
Call: Second Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
The main objective of this subject is to provide students with the minimum knowledge necessary to solve problems in the field of real-time intelligent systems, and the proper understanding of how to approach the resolution of such problems, but paying special attention to the handling of real time.
Real time systems. Determinism and reliability. Parallelism. Planning. Implementation languages.
Basic:
Alan Burns, Andy Wellings, Sistemas de tiempo real y lenguajes de programación, 9788478290581, 3ª, Addison-
Wesley, 2003
Complementary:
Manuel I. Capel Tuñón, Programación Concurrente y en tiempo real: Fundamentos y aplicaciones, 9788417289362,
Garceta, 2022
Rafael H. Bordini, Jomi Fred Hübner, Michael Wooldridge, Programming Multi-agent systems in Agent-Speak with
Jason, 10.1002/9780470061848, Wiley, 2007
Olivier Boissier, Rafael H. Bordini, Jomi Hubner, Alessandro Ricci, Multi-Agent Oriented Programming: Programming
Multi-Agent Systems Using JaCaMo, 9780262044578, MIT Press, 2020
BASIC AND GENERAL
GC1 - Maintain and extend sound theoretical approaches to enable the introduction and
exploitation of new and advanced technologies in the field of Artificial Intelligence.
GC2 - Successfully address all stages of an Artificial Intelligence project.
CG5 - Work in teams, especially multidisciplinary ones, and be skilled in time
management, people and decision making.
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 acquired knowledge and problem-solving skills
in new or unfamiliar environments within broader (or multidisciplinary) contexts related
to their area of study.
CB9 - Students should be able to communicate their conclusions and the knowledge and
rationale behind them to specialized and non-specialized audiences in a clear and
unambiguous manner.
CB10 - That students possess the learning skills that will allow them to continue
studying in a way that will be largely self-directed or autonomous.
TRANSVERSALS
CT3 - Use the basic tools of information and communication technologies (ICT)
necessary for the exercise of their profession and for lifelong learning.
CT7 - Develop the ability to work in interdisciplinary or transdisciplinary teams, to
offer proposals that contribute to sustainable environmental, economic, political and
social development.
CT8 - Value the importance of research, innovation and technological development in
the socioeconomic and cultural progress of society.
CT9 - Have the ability to manage time and resources: develop plans, prioritize
activities, identify critical ones, set deadlines and meet them.
SPECIFIC
CE19 - Knowledge of different fields of application of AI-based technologies and their
ability to offer a differentiating added value.
SC20 - Ability to combine and adapt different techniques, extrapolating knowledge
between different application areas.
SC21 - Knowledge of techniques that facilitate the organization and management of AI
projects in real environments, resource management and task planning in an efficient
way, taking into account concepts of knowledge dissemination and open science.
CE22 - Knowledge of techniques that facilitate the security of data, applications and
communications and their implications in different fields of application of AI.
CE30 - To be able to pose, model and solve problems that require the application of
artificial intelligence methods, techniques and technologies.
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.
The assessment will consist of three parts:
- Knowledge comprehension test, with a weighting of 30% of the final grade. It will consist of the presentation of a video and a memory with its own solution to a proposed exercise. This methodological test is compulsory in order to pass the subject, whether the continuous evaluation is followed or not. To pass this part of the evaluation, the student must obtain 5 points or more in his grade. The late deliveries and those that are delivered in a different format from the order will be valued with 0.
- Continuous monitoring of the subject, with a weighting of 30% of the final grade. At the end of each topic problems/exercises will be proposed that will serve for an evaluation through a continuous monitoring of the subject. To release this evaluation test, the student must obtain 5 points or more in his final grade. In case of not opting for the continuous evaluation, on the date of the exam the students will be able to answer the exercises that are presented.
- Project-based learning, with a weighting of 40% of the final grade: The solution (code + explanatory memory) to a proposed and assigned practical project will be evaluated. This test will be evaluated with the applications provided for its realization in groups of 2 people. This methodological test is compulsory, whether the continuous evaluation is followed or not. The delivery must be made on the dates and in the manner indicated. Late deliveries and those that are delivered in a different format than the one requested will be valued with 0. The delivery may require a defense by the members of the group on the date and in the manner indicated. To pass this evaluation test, the student must obtain 5 points or more in his/her final grade.
Since the default evaluation system is CONTINUOUS EVALUATION, it is considered that all students enrolled opt for this system. In case of not opting for this evaluation system, once the period of one month from the beginning of the term has passed, a period of 5 working days will be allowed for the students enrolled in the subject to formally express their intention of not opting for this system of CONTINUOUS EVALUATION. In this case, the test will consist of three parts:
- Theory Exam, with a weighting of 30%: Objective test that will include the evaluation of the theoretical concepts seen throughout the course and resolution of exercises/problems proposed in the Continuous Assessment System. In order to pass this part of the subject the student must obtain a qualification equal to or higher than 5 points (out of 10).
- Study of cases by means of the elaboration of Memory and Video, with a weighting of 30%: Elaboration of a video and a brief memory that presents/defends the solution of the student to a case of study that is determined, the work will be delivered in the date that is determined previous to that of the final Exam. In order to pass this part of the course, the student must obtain a grade equal to or higher than 5 points (out of 10) in the evaluation of both the report and the video. A late delivery or one that does not adjust to the parameters fixed for the delivery will be graded with 0 points.
- Solution to a project through the development of a practice and a practice report, with a weighting of 40%: it will be proposed for students who use this system and must be delivered on the date (prior to the exam date) and form to be determined. The solution will consist of a code with the solution and a report explaining and defending @dito solution. In order to pass this part of the subject the student must obtain a qualification equal or superior to 5 points (out of 10) in the evaluation in both the code and the report. Once the delivery has been made, the defense of the work done may be required in order to verify the authorship of the same on the date of the exam by answering a series of questions related to the assigned Project.
Whether the continuous evaluation is followed or not, the final grade of the subject is calculated by weighted average of the previous tests, to be able to make the average the student must achieve at least a 4 in each of the tests. If at the end of the course, a student presents a qualification lower than 4 in one or more of the previous tests, his qualification will be determined by the minimum value between the average of the marks of the above mentioned tests and four. All the deliveries of the previous tests that are not made on time and in the requested form will be graded with a 0. The evaluation criteria for the 2nd opportunity will be the same as for the first opportunity.
A1: Theory classes: 10 classroom hours, 20 hours total dedication.
A2: Practical laboratory classes: 7 classroom hours, 28 hours total dedication.
A3: Problem-based learning, seminars, case studies and projects: 4 classroom hours, 27
hours total dedication.
This course is offered by the University of Vigo.
Subjects recommended to have taken previously:
Multi-axis systems
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| 15:30-17:00 | Grupo /CLE_01 | English | IA.02 |
| 06.04.2025 16:00-20:00 | Grupo /CLIL_01 | IA.02 |
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