- Hopfield-Tank network
- 'Heatmap image' generation for given step
- 'Heatmap over time' video generation (very usefull for debuging)
Programs supports commandline interface which allows to run network once, or multiple times in a row. Properties of the network can be configured with arguments
-h, --help show this help message and exit
--steps [STEPS] Number of steps to take.
--freq [FREQ] Frequency of taking snapshots.
--seeds [SEEDS [SEEDS ...]]
Seed for random. Defines whole run.
--size-adjs [SIZE_ADJS [SIZE_ADJS ...]]
specifies value of size adjustment
--tag [TAG] tag added to name
- Matplotlib
- numpy
- ffmpeg
Implementation of Hopfield-Tank model for TSP. Project for my University Course.
Current version requires careful tuning of parameters to create feasible solutions. Look up page 16, second paragraph in following paper: http://www.iro.umontreal.ca/~dift6751/paper_potvin_nn_tsp.pdf
Based on following article by John J Hopfield and D W Tank: https://www.researchgate.net/publication/19135224_Neural_Computation_of_Decisions_in_Optimization_Problems Mainly equations and constants from 4'th paragraph were used.
- Maciej Staniuk
- Mateusz Albecki