Computer Science

General goals: The course will make students aware of the challenges behind the design, implementation and field use of autonomous networking systems. The course will present both the theoretical foundations and practical aspects you need to know to develop such systems. Specific goals: The combination of many heterogeneous connected devices, including fast moving devices, and advanced communication capabilities that enable real-time interactions is leading to the creation of systems on a scale and/or complexity level that is beyond the ability of humans to fully comprehend and control. Management and operation of these networking systems require an extremely high degree of intelligent automation. Goal of this course is to provide knowledge about the main network-related technologies whose interplay will be responsible for making networking systems autonomous. These technologies, mainly based on reinforcement learning (RL), allow systems react to what is occurring in their environment and respond accordingly. Knowledge and comprehension: At the end of the course students will have knowledge on the technologies and methodologies to design autonomous networks. Specifically, the course will focus on communication and networking issues of autonomous networks and possible solutions. Applying knowledge and understanding: The course will provide students the tools to understand when and how learning techniques can be applied to make a system adaptive and autonomous Critiquing and judgmental skills: Students will acquire the skills to review and analyse the design of autonomous networks. Communication skills: Students will acquire the skills to analyse and present scientific papers and research directions with proper language.