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

README.md


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.

alt text

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

alt text

comparing range of target values between

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

alt text

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