lunar-mining ba80aa439c lotterysim: add inflation rate analytics před 3 roky
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blockchain_scripts bd78bdaa45 [research/lotterysim] reorg lotterysim, acc_staked_ratio plot added před 3 roky
core ba80aa439c lotterysim: add inflation rate analytics před 3 roky
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log 242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging před 3 roky
pid 242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging před 3 roky
reports fe1c82bec0 [research/lotterysim/reports] update cascade report with simulation params, change title před 3 roky
search_space dee4a65777 [research/lotterysim] merge controllers před 3 roky
README.md 03a2aac436 lotterysim: create config.py. před 3 roky
__init__.py bd78bdaa45 [research/lotterysim] reorg lotterysim, acc_staked_ratio plot added před 3 roky
acc_vs_staked_ratio.py 6916f7c4c1 [research/lotterysim/reports] finalize report před 3 roky
config.py 03a2aac436 lotterysim: create config.py. před 3 roky
discrete_instance.py 242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging před 3 roky
draw.py 242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging před 3 roky
example.csv ede647e1d5 lotterysim: add example.csv před 3 roky
metrics.py ba80aa439c lotterysim: add inflation rate analytics před 3 roky
playground.ipynb 242060eac2 [research/lotterysim] update vesting, fix vesting apr, enhance logging před 3 roky
primary_discrete_auto_crawler.py 6916f7c4c1 [research/lotterysim/reports] finalize report před 3 roky
secondary_discrete_auto_crawler.py 2f497332f9 [research/lotterysim] replace apy with apr před 3 roky
secondary_takahashi_auto_crawler.py 2f497332f9 [research/lotterysim] replace apy with apr před 3 roky
takahashi_instance.py 2f497332f9 [research/lotterysim] replace apy with apr před 3 roky
vesting.py ba80aa439c lotterysim: add inflation rate analytics před 3 roky

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