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  • Āut Labs
  • The Āutonomy Matrix
  • $AUT Token
  • Framework Intro & Components
    • Āutonomy Matrix
    • The Participation Score
      • More about Expected Contributions
    • ĀutID: a Member< >Hub bond
    • Interactions, Tasks & Contributions - a context-agnostic standard.
    • Contribution Points
      • Calculating eCP and other dependent & independent params
    • The Hub - or, the whole is greater than the sum of its parts.
    • Roles on-chain. If there is Hope, it lies in the Roles
    • Commitment Level as an RWA
      • Discrete CL Allocation
    • Peer Value
      • Flow & aggregation of value
  • 🕹️Participation Score
    • Design Thinking
      • Problems with traditional Local Reputation parameters
      • Innovation Compared to other “Local Reputation” protocols
      • Hub<>Participant Accountability & Rewards
    • Core Parameters
    • Formulæ
    • Edge Cases
      • 1. The Private Island
      • 2. Cannibal Members
      • 3. The Ghost & the House on Fire
    • PS Formula for all Edge Cases
    • Conclusions
  • 🎇Prestige
    • Prestige: introducing measurable credibility for a DAO
    • Need for a DAO to measure its KPIs overtime (on-chain)
    • Archetypes
      • Defining an Organizational Type
      • Existing Organizational Types
      • Deep-dive: Calculating current Parameters (p)
    • Formulas for Prestige
      • Normalization of p
    • Prestige for all edge cases
      • Relationship between Prestige & Archetype parameters
    • How to expand Prestige through external Data Sources
    • Use-cases & Conclusions
  • 🌎Peer Value
    • Initial Applications
    • Relationship between Participant, Hubs & Peer Value
    • Peer Value (v) as a directed graph
      • Calculating normalized Participation Score (PS'')
      • Calculating normalized Prestige (P'')
      • Calculating the Contributor Archetype (a)
    • The Peer archetype
      • Formulæ for α & deep-dives
      • Formulæ for β & deep-dives
      • Formulæ for γ & deep-dives
    • Conclusions & Initial Applications
  • ⚽Appendices & Playgrounds
    • PS Simulations
    • PS Playground
    • Prestige Simulations
    • Prestige Playground
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On this page
  • 1. Repeat the Simulation
  • 2. Create a new simulation, step-by-step
  1. Appendices & Playgrounds

Prestige Playground

PreviousPrestige Simulations

Last updated 10 months ago

you can download the spreadsheet with existing simulation and guidance to build new ones.

1. Repeat the Simulation

  1. Define the number of periods (e.g., 10) and the number of Hubs (e.g., 3) you want to include in the simulation.

  2. Set the fixed values for the simulation:

    • Initial Prestige ( P0\mathfrak{P}_{\tiny 0}P0​) for all Hubs (e.g., 100)

    • Constraint factor ( c) (e.g., 1.4)

    • Penalty factor ( p⊖p_{\tiny \ominus}p⊖​) (e.g., 0.4)

  3. For each Hub, assign an (e.g., Size, Performance, Conviction) and set the corresponding weights for each parameter -> wSundefined, wPS‾, wiCL‾, wP→, wGˇw_{\tiny \overlinesegment S} \text{, } w_{\tiny \overline{PS}}\text{, } w_{\tiny \overline{iCL}} \text{, } w_{\tiny \overrightarrow{P}} \text{, } w_{\tiny \check{G}}wS​, wPS​, wiCL​, wP​, wGˇ​ based on the chosen archetype. Ensure that the sum of the weights equals 1.

  4. For each period and each Hub, assign values to the parameters:

    • Total Community Members (TCM)

    • Average Member Participation Score ( PS‾\overline{PS}PS)

    • Average Commitment Level ( iCL‾\overline{iCL}iCL)

    • Community Performance ( P→\overrightarrow{P}P)

    • Community Growth ( Gˇ\check{G} Gˇ), calculated as the percentage change in TCM from the previous period

  5. Normalize the parameter values:

    • TCM: Divide each Hub's TCM by the highest TCM value across all periods and Hubs

    • PS‾, iCL‾, P→\overline{PS} \text{, } \overline{iCL} \text{, } \overrightarrow{P}PS, iCL, P: Divide each value by the highest value (e.g., 1.00) across all periods and Hubs

    • Gˇ\check{G}Gˇ: Use the percentage change in TCM from the previous period.

  6. values for each Hub in each period.

K=∑p=1n(wp×p′)K = \displaystyle \sum_{p=1}^{n}(w_p \times p')K=p=1∑n​(wp​×p′)
  1. Analyze the results.

2. Create a new simulation, step-by-step

To create new simulations, you can:

  • Modify the number of periods and Hubs.

  • Change the fixed values (initial Prestige, constraint factor, penalty factor).

  • Assign different archetypes and weights to the Hubs

  • Introduce different stress factors by modifying the parameter values for each Hub in each period.

  • Experiment with different normalization methods or formulas for calculating $K$, $\Delta K$, and Prestige

By following these steps, you can create and analyze infinite scenarios to verify and better understand the behavior of the Prestige framework under different (stress) conditions.

Calculate the Prestige ( P\mathfrak{P}P) for each Hub in each period using the .

⚽
Here
archetype
Calculate the K & ΔK\Delta {K}ΔK
General Formula for Prestige