| Competencies / Study results |
| Code | Study programme competences / results |
| A8 | CE07 - Ability to understand the consequences of the development of an explainable and interpretable intelligent system |
| A9 | CE08 - Ability to design and develop secure intelligent systems, in terms of integrity, confidentiality and robustness |
| A10 | CE09 - Ability to obtain a deep knowledge about fundamental principles and models of quantum computing and to apply them for the interpretation, selection, evaluation, modelling and creation of new concepts, theories, uses and technological developments related to Artificial Intelligence |
| A14 | CE13 - Knowledge of computer tools in the field of data analysis and statistical modelling and ability to select those ones most suitable for problem solving |
| A15 | CE14 - Understanding and command of the main machine learning techniques, including those devised for big volumes of data. Understanding and command of basic concepts and techniques for information search and filtering in big collections of data. |
| A16 | CE15 - Knowledge of computer tools in the field of machine learning and ability to select those ones most suitable for problem solving |
| A20 | CE19 - Knowledge of the different environments where AI based technologies can be applied and awareness of their capability to provide a differentiating added value |
| A21 | CE20 - Ability to combine and adapt different techniques, extrapolating knowledge among different application domains |
| A22 | CE21 - Knowledge of the techniques that facilitate the efficient organisation and management of AI projects in real environments, including resources management and tasks scheduling and taking into account the concepts of knowledge dissemination and open science |
| A23 | CE22 - Knowledge of the techniques that facilitate the security of data, applications and communications and the derived consequences on different application domains in AI |
| A28 | CE27 - Understanding the significance of the entrepreneurial culture and knowledge of the resources within the enterpreneur person's means |
| A29 | CE28 - Appropriate knowledge of the concept of enterprise, its organisation and management, and of the different business sectors, with the goal of providing solutions from the AI perspective |
| A30 | CE29 - Being able to apply knowledge, abilities and attitudes to the business and professional world, by planning, managing and evaluating projects in the scope of AI |
| A31 | CE30 - Being able to set out, model and solve problems that require the application of AI methods, techniques and technologies |
| B1 | CG01 - Maintaining and extending theoretical foundations to allow the introduction and exploitation of new and advanced technologies in the field of AI |
| B2 | CG02 - Successfully addressing each and every stage of an AI project |
| B5 | CG05 - Working in teams, especially of multidisciplinary nature, and being skilled in the management of time, people and decision making |
| B6 | CB01 - Acquiring and understanding knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, frequently in a research context |
| B7 | CB02 - The students will be able to apply the acquired knowledge and to use their capacity of solving problems in new or poorly explored environments inside wider (or multidisciplinary) contexts related to their field of study |
| B9 | CB04 - The students will be able to communicate their conclusions, their premises and their ultimate justifications, both to specialised and non-specialised audiences, using a clear style language, free from ambiguities |
| B10 | CB05 - The students will acquire learning abilities to allow them to continue studying in way that will mostly be self-directed or autonomous |
| C2 | CT02 - Command in understanding and expression, both in oral and written forms, of a foreign language |
| C4 | CT04 - Acquiring a personal development for practicing a citizenship under observation of the democratic culture, the human rights and the gender perspective |
| C5 | CT05 - Understanding the importance of the entrepreneurial culture and knowledge of the resources within the entrepreneur person's means |
| C6 | CT06 - Acquiring abilities for life and healthy customs, routines and life styles |
| Learning aims | |||
| Learning outcomes | Study programme competences / results | ||
| Knowing the features and functions of a real-time system | AC7 AC8 AC9 AC13 AC14 AC15 AC19 AC20 AC21 AC22 |
BC1 BC2 BC5 BC6 BC9 BC10 |
CC2 CC4 CC5 CC6 |
| Ability to design and program a real-time system | AC7 AC8 AC9 AC13 AC14 AC15 AC19 AC22 AC27 |
BC7 BC9 BC10 |
CC2 CC4 CC5 CC6 |
| Knowing the most common programming languages for real-time systems, both synchronous and asynchronous | AC7 AC8 AC9 AC13 AC14 AC15 AC19 AC20 AC21 AC22 AC27 AC28 AC29 AC30 |
BC1 BC2 BC5 BC6 BC7 BC9 BC10 |
CC2 CC4 CC5 CC6 |
| Knowing how to develop trustable software components, with special emphasis on fail tolerance and error recovery | AC7 AC8 AC9 AC13 AC14 AC15 AC19 AC20 AC21 AC22 AC27 AC28 AC29 AC30 |
BC1 BC2 BC5 BC6 BC7 BC9 BC10 |
CC2 CC4 CC5 CC6 |
| Contents |
| Topic | Sub-topic |
| Sistemas de tiempo real. | Introducción. Diseño de STR. Sistemas Inteligentes en TR. |
| Determinismo y confiabilidad. | Determinismo. Fiabilidad. Tolerancia a fallos. Manejo de excepciones. |
| Paralelismo. | Concurrencia. Hipótesis síncrona y asíncrona. Tiempo Real. Planificación. Distribución. |
| Planificación | Estrategias. Verificación del comportamiento. Arquitecturas. |
| Lenguajes de implementación. | Lenguajes de uso general. Lenguajes basados en agentes. Simulación. |
| Planning | ||||
| Methodologies / tests | Competencies / Results | Teaching hours (in-person & virtual) | Student’s personal work hours | Total hours |
| Laboratory practice | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | 8 | 24 | 32 |
| Case study | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | 1 | 1 | 2 |
| Collaborative learning | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | 0 | 16 | 16 |
| Guest lecture / keynote speech | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | 12 | 12 | 24 |
| Personalized attention | 1 | 0 | 1 | |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
| Methodologies |
| Methodologies | Description |
| Laboratory practice | Practical work, normally in groups, with tools of real time systems |
| Case study | Se planteará al alumnado un escenario de trabajo, real o ficticio, que presenta una determinada problemática, para que este aplique los conocimientos adquiridos en la elaboración de una solución que será presentada mediante un vídeo de unos 10' de duración. EVALUACIÓN CONTINUA Carácter: Obligatorio Asistencia: Non Obligatoria EVALUACIÓN GLOBAL Carácter: Obligatorio |
| Collaborative learning | El profesor planteará al alumnado una serie de proyectos prácticos para su resolución utilizando los contenidos vistos tanto en teoría, como en el laboratorio. La solución estará compuesta por un código comentado y una memoria que describa adecuadamente la solución aportada. EVALUACIÓN CONTINUA Carácter: Obligatorio Asistencia: Non Obligatoria EVALUACIÓN GLOBAL Carácter: Obligatorio |
| Guest lecture / keynote speech | Classes of concepts and foundations with small exercises |
| Personalized attention |
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| Assessment | |||
| Methodologies | Competencies / Results | Description | Qualification |
| Guest lecture / keynote speech | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | Depending on how the course evolves, a part of the exam could be consolidated by submitting solved exercises along the lecture classes period | 30 |
| Case study | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | Presentación de un vídeo y una memoria con una solución propia a un caso de estudio propuesto. Esta prueba metodológica es obligatoria, tanto en evaluación continua como global. Para liberar esta parte de la evaluación, el estudiante debe obtener 5 puntos o más en su nota. Las entregas tardías y aquellas que se entreguen en un formato diferente al del pedido serán valoradas con 0. |
30 |
| Collaborative learning | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | Se evaluará la solución (código + memoria explicativa) a un proyecto práctico propuesto y asignado. Esta prueba se evaluará con las aplicaciones proporcionadas para su realización en grupos de 2 personas. Esta prueba metodológica es obligatoria, tanto en evaluación continua como global. La entrega deberá realizarse en las fechas y en la forma indicadas. Las entregas tardías y aquellas que se entreguen en un formato diferente al solicitado serán valoradas con 0. La entrega podrá requerir una defensa por parte de los integrantes del grupo en la fecha y forma que se indiquen. Para liberar esta prueba de evaluación, el estudiante debe obtener 5 puntos o más en su calificación final. |
40 |
| Assessment comments | |||
| Sources of information |
| Basic |
Olivier Boissier, Rafael H. Bordini, Jomi Hubner, Alessandro Ricci (2020). Multi-Agent Oriented Programming: Programming Multi-Agent Systems Using JaCaMo. MIT Press
Manuel I. Capel Tuñón (2022). Programación Concurrente y en tiempo real: Fundamentos y aplicaciones. Garceta
Rafael H. Bordini, Jomi Fred Hübner, Michael Wooldridge (2007). Programming Multi-agent systems in Agent-Speak with Jason. Wiley
Alan Burns, Andy Wellings (2003). Sistemas de tiempo real y lenguajes de programación. Addison-Wesley |
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