Commit fd0727fd authored by Grégoire Grzeczkowicz's avatar Grégoire Grzeczkowicz
Browse files

Add informations

parent 61a8d4e5
......@@ -127,9 +127,21 @@ Most exercises consists in adding a single function in an existing module
2. Implement an evolutionary algorithm.
You can use `num_genetic` or `bit_genetic`
3. Implement an expected run time empirical cumulative density function.
You can call `draw_ert.py` with -N option for the number of run and -v option to choose a target value
You can execute `ert.py` which will plot 3 ert for two algorithms.
You can also use `draw_ert.py` with -N option for the number of run and optionally -v option to choose a target value (if not use will draw a surface for all target)
4. Implement a simple design of experiment to determine the best solver.
You can use `try_solver.py` to list the different parameter you want to try and get the best parameter
You can use `try_solver.py` to list the different parameter you want to try and get the best parameter (parameter inside the script)
5. Provide a solver for a competition.
For the competion, symply use my `num_greedy`
For the competion, symply use my `snp.py`.
I have had the following penalisation to `num.py` :
```python3
if len(sol) > dim:
s *= 0.5
for v in sol:
if v < 0:
s += v/domain_width
if v >= domain_width:
s -= (v-domain_width)/domain_width
```
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