skoupidi 8c33d59f40 chore: updated all repo references to codeberg		2 tahun lalu
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.ipynb_checkpoints	242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging	3 tahun lalu
blockchain_scripts	bd78bdaa45 [research/lotterysim] reorg lotterysim, acc_staked_ratio plot added	3 tahun lalu
core	6e6bf0ba33 [research/lotterysim] fix update vesting, and negative apr	3 tahun lalu
img	35405831e3 [research/lotterysim] simulate transaction fee, and tipless mechanism, with controlled pid	3 tahun lalu
pid	a7d2776ac4 [research/lotterysim] add base fee controller crawler for tuning	3 tahun lalu
reports	8c33d59f40 chore: updated all repo references to codeberg	2 tahun lalu
search_space	dee4a65777 [research/lotterysim] merge controllers	3 tahun lalu
.gitignore	6318c2bd76 script/research/lotterysim: .gitignore added	3 tahun lalu
README.md	8c33d59f40 chore: updated all repo references to codeberg	2 tahun lalu
__init__.py	bd78bdaa45 [research/lotterysim] reorg lotterysim, acc_staked_ratio plot added	3 tahun lalu
acc_vs_staked_ratio.py	fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts	3 tahun lalu
acc_vs_staked_ratio_pi.py	fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts	3 tahun lalu
acc_vs_staked_ratio_pi_headstart.py	d7f477e4f9 [research/lotterysim] headstart, remove airdrop	3 tahun lalu
basefee_discrete_autocrawler_pi.py	a7d2776ac4 [research/lotterysim] add base fee controller crawler for tuning	3 tahun lalu
config.py	03a2aac436 lotterysim: create config.py.	3 tahun lalu
discrete_instance.py	6e6bf0ba33 [research/lotterysim] fix update vesting, and negative apr	3 tahun lalu
discrete_instance_pi_headstart.py	635c326c17 [research/lotterysim] fix drop in accuracy after 0mint distribution ends; starting with 0 premint at genesis/pre-genesis	3 tahun lalu
draw.py	242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging	3 tahun lalu
example.csv	ede647e1d5 lotterysim: add example.csv	3 tahun lalu
metrics.py	3aaf7e466c [research/lotterysim] handle 0 premint divin by zero case]	3 tahun lalu
playground.ipynb	242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging	3 tahun lalu
plot_darkies.py	6e6bf0ba33 [research/lotterysim] fix update vesting, and negative apr	3 tahun lalu
pool_advantage.py	2e2aff3919 [reesarch/lotterysim] pool zero advantage demonestration	3 tahun lalu
primary_discrete_auto_crawler.py	f0a4095833 [research/lotterysim] simulate timelocked airdrop, enhance log	3 tahun lalu
primary_discrete_auto_crawler_pi.py	2a0a9d84b8 [research/lotterysim] update crawlers, re-tune controllers for better acc, and stable apr	3 tahun lalu
secondary_discrete_auto_crawler.py	2a0a9d84b8 [research/lotterysim] update crawlers, re-tune controllers for better acc, and stable apr	3 tahun lalu
secondary_discrete_auto_crawler_pi.py	2a0a9d84b8 [research/lotterysim] update crawlers, re-tune controllers for better acc, and stable apr	3 tahun lalu
secondary_takahashi_auto_crawler.py	2f497332f9 [research/lotterysim] replace apy with apr	3 tahun lalu
takahashi_instance.py	2f497332f9 [research/lotterysim] replace apy with apr	3 tahun lalu
vesting.py	d60d72d088 [research/lotterysim] update vesting darkie id	3 tahun lalu

title: darkfi lottery simulation author: ertosns

date: 11/1/2023

simulate darkfi consensus lottery with a discrete controller

discrete pid controller.

control lottery f tunning paramter

$$f[k] = f[k-1] + K_1e[k] + K_2e[k-1] + K_3e[k-2]$$

with $k_1 = k_p + K_i + K_d$, $k_2 = -K_p -2K_d$, $k_3 = K_d$, and e is the error function.

simulation criterion

find $K_p$, $k_i$, $K_d$ for highest accuracy running the simulation on N trials, of random number of nodes, starting with random airdrop (that all sum to total network stake), running for random runing time.

notice that best parameters are spread out in the search space, picking the highest of which, and running the simulation, running for 600 slots, result in with >36% accuracy

comparing range of target values between

notice below that both y,T in the pallas field, and simulation have same range.

conclusion

using discrete controller the lottery accuracy > 33% with randomized number of nodes, and randomized relative stake. can be coupled with khonsu^1 to achieve 100% accuracy and instant finality.

usage

Replace example.csv with local distribution data. Edit config.py as follows:

vesting_file = 'your_local_data.csv'

Edit config.py to define the exchange rate and simulation running time, measured in slots.

Then run the program:

python vesting.py

README.md