Degree | Type | Year |
---|---|---|
2504392 Artificial Intelligence | OB | 3 |
You can view this information at the end of this document.
Conceptual knowledge or Basics of programming, Computational logic, machine learning, neural networks and deep learning.
This subject introduces the basics of autonomous agents, gives a detailed vision of the design of these agents and provides the foundations for programming them in industrial or service production environments, integrating different elements learned throughout the degree.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Classroom lectures | 30 | 1.2 | 3, 4, 5, 9, 10, 12 |
Classroom practices | 15 | 0.6 | 2, 4, 6, 12 |
Type: Supervised | |||
Scheduled group tutorials | 50 | 2 | 2, 6, 12, 14 |
Type: Autonomous | |||
Individual preparation of written tests | 13 | 0.52 | 2, 3, 4, 9, 10, 12 |
Teamwork | 30 | 1.2 | 2, 4, 6, 12, 14 |
Text readings | 10 | 0.4 | 2, 3, 5, 9, 10, 12 |
Since the subject is mainly oriented to the learning of the basic techniques of designing and building software authonomous agents, the teaching methodology and the formative activities of the subject will combine: expositive lecture sessions (to guide and clarify doubts about compulsory readings), face-to-face practices (in classroom, in seminars, or in computer rooms), and applied teamwork. This teaching format allows to apply the concepts acquired and techniques explained, and will be combined throughout the course with tutorials of follow-up and autonomous work.
As the core of a challenge-based learning process, an Agents’ Challenge Arena (ACA) will be organised to test the performance of the different teamwork projects.
Following are the different activities, with their specific weight within the distribution of the total time that the student has to dedicate to the subject.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Practical works | 50% | 0 | 0 | 1, 2, 4, 6, 7, 8, 9, 11, 12, 13, 14 |
Theory related written test 1st part | 25% | 1 | 0.04 | 2, 3, 4, 5, 9, 10, 12 |
Theory related written test 2nd part | 25% | 1 | 0.04 | 2, 3, 4, 5, 9, 10, 12 |
The assessment of each student's level of achievement in the course takes into account the practical work, as well as the scientific and technical knowledge of the course. The final grade reflects this by combining the scores from the practical and theoretical parts as follows:
(a) Theory test (1st exam) (25%)
(b) Theory test (2nd exam) (25%)
(c) Practical exercises (50%)
To pass the course in the first examination period, it is mandatory to obtain at least a grade of 5 in each of the evaluation items (a), (b), and (c). The final grade will be calculated as a weighted average of all the evaluation items.
In the second examination period, it is possible to retake evaluation items (a), (b), and (c) where the grades were below 5. To successfully pass the course in the second examination period, a minimum grade of 5 must be achieved in the retaken items. Additionally, it is important to note that the grade assigned to the retaken evaluation item will be 5 (even if the final score is higher).
Not Evaluated: The student's final grade will be "Not Presented" if the student has not been evaluated in the written tests (a) and (b).
Honors: The award of an "Honors" title (MH) is at the discretion of the course faculty. The UAB regulations state that the honors title can only be awarded to students who have obtained a final grade equal to or greater than 9, and only up to 5% of the total enrolled students can be awarded an honors title.
Plagiarism: Without prejudice to other measures deemed appropriate and in accordance with current academic legislation, irregularities committed by a student during an assessment activity may result in the grade being changed to 0. Evaluation activities thus graded by this procedure will not be recoverable. If it is necessary to pass any of these assessment activities to pass the course, the student will not pass the course, without the possibility of retaking it in the second examination period of the same academicyear. These irregularities include, among others:
In the event that the student has committed irregularities in any assessment activity (and therefore will not be able to pass the course even in the second examination period), the final grade for the course will be the lower of either 3 or the weighted average of the grades. In summary: copying, allowing others to copy your work, or plagiarizing in any of the assessment activities equates to failing with a grade of 3 or lower.
Bordini R. H. Hübner Jomi Fred & Wooldridge M. J. (2007). Programming multi-agent systems in agentspeak using jason. Wiley Series in Agent Technology. J. Wiley.
Russell S. J. Norvig P. Chang M.-W. Devlin J. Dragan A. Forsyth D. Goodfellow I. Malik J. Mansinghka V. & Pearl J. (2022). Artificial intelligence: a modern approach (Fourth edition. Global). Pearson.
Wooldridge M. J. (2009). An introduction to multiagent systems (2. ed.). John Wiley & Sons.
PyCharm ( or another IDE ), JASON, PYTHON, UNITY, NETLOGO.
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PAUL) Classroom practices | 1 | English | second semester | afternoon |
(PLAB) Practical laboratories | 1 | English | second semester | afternoon |
(PLAB) Practical laboratories | 2 | English | second semester | afternoon |
(TE) Theory | 1 | English | second semester | afternoon |