ertosns f20c88b2f1 [research/lotterysim] emulate slashing as random process with certain low probability 3 жил өмнө
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.ipynb_checkpoints 242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging 3 жил өмнө
blockchain_scripts bd78bdaa45 [research/lotterysim] reorg lotterysim, acc_staked_ratio plot added 3 жил өмнө
core f20c88b2f1 [research/lotterysim] emulate slashing as random process with certain low probability 3 жил өмнө
img b3a868999d [research/lotterysim] plot from ./log initial stake, apr for each node in plot_darkies.py 3 жил өмнө
pid 26809109ce script/research/lotterysim/pid/pid.md: further fixed total tokens calculation 3 жил өмнө
reports fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts 3 жил өмнө
search_space dee4a65777 [research/lotterysim] merge controllers 3 жил өмнө
.gitignore 6318c2bd76 script/research/lotterysim: .gitignore added 3 жил өмнө
README.md 03a2aac436 lotterysim: create config.py. 3 жил өмнө
__init__.py bd78bdaa45 [research/lotterysim] reorg lotterysim, acc_staked_ratio plot added 3 жил өмнө
acc_vs_staked_ratio.py fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts 3 жил өмнө
acc_vs_staked_ratio_pi.py fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts 3 жил өмнө
acc_vs_staked_ratio_pi_headstart.py d7f477e4f9 [research/lotterysim] headstart, remove airdrop 3 жил өмнө
config.py 03a2aac436 lotterysim: create config.py. 3 жил өмнө
discrete_instance.py fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts 3 жил өмнө
discrete_instance_pi_headstart.py f20c88b2f1 [research/lotterysim] emulate slashing as random process with certain low probability 3 жил өмнө
draw.py 242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging 3 жил өмнө
example.csv ede647e1d5 lotterysim: add example.csv 3 жил өмнө
metrics.py ba80aa439c lotterysim: add inflation rate analytics 3 жил өмнө
playground.ipynb 242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging 3 жил өмнө
plot_darkies.py e9e2de886d [research/lotterysim] update Sigma (total stake) with primary reward with headstart 3 жил өмнө
pool_advantage.py 2e2aff3919 [reesarch/lotterysim] pool zero advantage demonestration 3 жил өмнө
primary_discrete_auto_crawler.py 5f44e59bb1 [research/lotterysim] bug fixed with cascade control, round primary feedback precision to .2f 3 жил өмнө
primary_discrete_auto_crawler_pi.py fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts 3 жил өмнө
secondary_discrete_auto_crawler.py fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts 3 жил өмнө
secondary_discrete_auto_crawler_pi.py fc012bb2c4 [research/lotterysim] update cascade report with pi vs pid, and pi scripts 3 жил өмнө
secondary_takahashi_auto_crawler.py 2f497332f9 [research/lotterysim] replace apy with apr 3 жил өмнө
takahashi_instance.py 2f497332f9 [research/lotterysim] replace apy with apr 3 жил өмнө
vesting.py ba80aa439c lotterysim: add inflation rate analytics 3 жил өмнө

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