Programming

The goal of the subject is to provide the student with enough ability and knowledge about agents and multiagent systems through its application on a real problem. The domain of problems where agents are applied often have distributed nature, require privacy, intelligence and planning. Students have to apply the principles, methods and techniques of agents into the chosen problem

- Introduction to agents: basic concepts and its role in actual AI. - Identifying key aspects of a problem domain from the agent perspective: Designing an agent system - Communication and coordination among agents: FIPA - Intelligence of agents: BDI - Electronic Institutions: Norms and obligations. - LLM Agents and its adaptation to the agent foundations.

Learning activities: * Theoretical lectures: Mainly oriented to the acquisition of the theoretical knowledge of the subject' competences * Practical lectures: Mainly oriented to problem solving. * Partial exams: Oriented to prove the understanding of theoretical lectures * Practical teamwork: Oriented to prove the understanding of practical lectures, and towards the competences related to work in teams in a practical case. organization and written communication (in written reports) * (online or onsite) Personal Tutoring (asked by email in advance) Methodology: * Oral lectures in classroom * Teamwork * Problem solving