Research Seminar on Evolutionary and Complex Systems

Year
1
Academic year
2019-2020
Code
03018996
Subject Area
Optional Specialties
Language of Instruction
Portuguese
Other Languages of Instruction
English
Mode of Delivery
Face-to-face
Duration
SEMESTRIAL
ECTS Credits
9.0
Type
Elective
Level
3rd Cycle Studies

Recommended Prerequisites

Current Topics on Intelligent Systems (1st semester, 9 ECTS, elective); Research Methods I (1st semester, 6 ECTS, mandatory)

The enrollment in the course is subject to approval by the Coordination of the Doctoral Program

Teaching Methods

 

Three complementary activities will be carried out:

 

1 - Lectures (9h): to introduce to current topics in the scientific area.

 

2 - Seminars (24h): presentation and discussion of scientific papers by students.

 

3 – Elaboration of a paper, peer-reviewing, presentation and discussion in a workshop.

 

Evaluation:

- Presentations in comp. 1: 25%

- Discussions in comp. 2 and 3, quality of revisions in comp. 3: 25%

- Paper of comp. 3 (overall quality, presentation, discussion): 50%

 

Attendance to 75% of the total classes is mandatory.

Learning Outcomes

-          To obtain an overview of the state of the art and main research challenges of the scientific area of the course.

-          To obtain knowledge and understanding about research projects and topics of the scientific area of the course under different perspectives, including scientific, methodological, management and communication.

-          To improve competences of critical analysis of scientific works, synthesis, scientific writing, verbal and writen communication, critical reasoning, autonomous learning, research and group integration.

Work Placement(s)

No

Syllabus

 

Advanced topics in the following areas will be addressed:

 

  1. Evolutionary Computation and Complex Systems
  2. Design and Validation of Experiments
  3. Combinatorial Optimization: exact and heuristic approaches
  4. Parameter Setting of Evolutionary Algorithms
  5. Multi-Objective Algorithms
  6. Representation and Evolvability
  7. Evolution of the Components of an Evolutionary Algorithm
  8. Emergence of Complexity
  9. Machine Learning and Evolutionary Algorithms
  10. Open Questions in Evolutionary Computation  and Complex Systems

 

Other topics may be analysed and discussed, within the general area of communications and telematics, depending on their interest to the achievement of the course objectives.

Head Lecturer(s)

Carlos Manuel Mira da Fonseca

Assessment Methods

Assessment
Synthesis work: 50.0%
Report of a seminar or field trip: 50.0%

Bibliography

 

Para cada tópico desta cadeira será facultada aos alunos  bibliografia específica. Tal não preclude a consulta prévia de textos genéricos de iniciação à área em função das necessidades dos alunos:

  1. A. Gaspar-Cunha,R. Takahashi, C. H. Antunes, Manual de Computação Evolutiva e Meta-Heurísticas, IUC, 2012
  2. A. Brabazon, M. O’Neil, S. McGarraghy, Natural Computing Algorithms, Springer,2015.
  3. H. Sayama, Introduction to the Modeling and Analysis of Complex Systems, SUNY, 2015.

 

For each topic to be addressed in the course, a list of research papers will be provided to the students. This does not preclude the previous consultation of general text books in Evolutionary and Complex Systems, depending on students’ needs:

 

  1. A. Gaspar-Cunha,R. Takahashi, C. H. Antunes, Manual de Computação Evolutiva e Meta-Heurísticas, IUC, 2012
  2. A. Brabazon, M. O’Neil, S. McGarraghy, Natural Computing Algorithms, Springer,2015.
  3. H. Sayama, Introduction to the Modeling and Analysis of Complex Systems, SUNY, 2015.