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Coursebooks
Distributed intelligent systems
ENG-466
Lecturer(s) :
Martinoli AlcherioLanguage:
English
Withdrawal
It is not allowed to withdraw from this subject after the registration deadline.Summary
The goal of this course is to provide methods and tools for modeling distributed intelligent systems as well as designing and optimizing coordination strategies. The course is a well-balanced mixture of theory and practical activities using simulation and real hardware platforms.Content
- Introduction to key concepts such as self-organization and software and hardware tools used in the course
- Examples of natural, artificial and hybrid distributed intelligent systems
- Modeling methods: sub-microscopic, microscopic, macroscopic, multi-level; spatial and non-spatial; mean field, approximated and exact approaches
- Machine-learning methods: single- and multi-agent techniques; expensive optimization problems and noise resistance
- Coordination strategies and distributed control: direct and indirect schemes; algorithms and methods; performance evaluation
- Application examples in distributed sensing and action
Keywords
Artificial intelligence, swarm intelligence, distributed robotics, sensor networks, modeling, machine-learning, control
Learning Prerequisites
Required courses
Fundamentals in analysis, probability, and programming for both compiled and interpreted languages
Recommended courses
Basic knowledge in statistics, specific programming language used in the course (C and Matlab), and signals and systems
Learning Outcomes
By the end of the course, the student must be able to:- Design a reactive control algorithm
- Formulate a model at different level of abstraction for a distributed intelligent system
- Analyze a model of a distributed intelligent system
- Analyze a distributed coordination strategy/algorithm
- Design a distributed coordination strategy/algorithm
- Implement code for single robot and multi-robot systems
- Carry out systematic performance evaluation of a distributed intelligent system
- Apply modeling and design methods to specific problems requiring distributed sensing and action
- Optimize a controller or a set of possibly coordinated controllers using model-based or data-driven methods
Transversal skills
- Demonstrate a capacity for creativity.
- Access and evaluate appropriate sources of information.
- Collect data.
- Plan and carry out activities in a way which makes optimal use of available time and other resources.
- Make an oral presentation.
- Write a scientific or technical report.
- Evaluate one's own performance in the team, receive and respond appropriately to feedback.
Teaching methods
Ex-cathedra lectures, assisted exercises with in-term verification, and a course project involving teamwork
Expected student activities
Attending lectures, carrying out exercises and the course project, and reading handouts.
Assessment methods
Continuous control (50%) with final written exam (50%).
Supervision
Office hours | Yes |
Assistants | Yes |
Forum | No |
Resources
Bibliography
Lecture notes, selected papers and book chapters distributed at each lecture.
Websites
Moodle Link
Prerequisite for
R&D activities in engineering
In the programs
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- Energy Management and Sustainability, 2019-2020, Master semester 1
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- Energy Management and Sustainability, 2019-2020, Master semester 3
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
- SemesterFall
- Exam formWritten
- Credits
5 - Subject examined
Distributed intelligent systems - Number of places
60 - Lecture
2 Hour(s) per week x 14 weeks - Exercises
3 Hour(s) per week x 14 weeks
- Semester
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