This page is located in archive.


Each student will work on an assignment. The assignment consists of:

  • report in English (preferred) or Czech: 20 points (min 10 points), guidelines for writing the report are listed below
  • implementation (any programming language is possible): 10 points,

Use exclusively the following templates for writing your report:

Use Upload system to submit the assignment.

Deadline for the program implementation is May 19, 11:00 am.

Deadline for the report submission is May 26, 11:00 am.

Guidelines for writing the report


  • Only the templates provided must be used. A report not using the template will not be accepted.
  • Pay attention to the clarity of the text so that it is properly structured and formatted.
  • Do not be unduly concise. Make sure that there is all information necessary to understand the text, especially the description of the proposed algorithms.
  • Report must start with a title specifying the solved problem and Author’s name.
  • Use references to tables, figures, literature.
  • As a technical report it must contain a list of References (the number of referred items is not important) at the end.

Description of the algorithm has to cover:

  • Description of a genetic representation of the solution
  • Definition of the fitness
  • Description of genetic operators, selection, construction heuristics, local optimization heuristics
  • Description of the evolutionary model, i.e., the process through which a new population is generated from the current one

For neural networks you have to cover:

  • Description of ANN topologies and neuron types used
  • Description of a learning algorithm (if you use a well-know algorithm a short description will suffice)
  • Description of inputs/outputs
  • Description of error measure (for supervised tasks)

Description of conducted experiments has to include:

  • Setting of the control parameters of compared algorithms
  • Number of runs conducted for each experiment
  • Definition of observed performance criteria (average best, mean best, standard deviation, …)
  • Presentation of the achieved results (in the form of tables and graphs)
  • Discussion of the observed algorithm performance

Graphs should

  • have all axes annotated
  • have a legend clearly distinguishing curves if there are more than one in a single plot
  • use proper scale so that the important trend in data is clearly presented

Extra points can be obtained for high quality English texts.

courses/a4m33bia/assignment.txt · Last modified: 2016/05/12 15:22 by kubalik