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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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  1. Appendices & Playgrounds

PS Simulations

Tests & Simulations - trust but verify

1. Stress factors [TCM + iCL]

  • Total Community Members (TCM) spike & drop

    • The simulation includes periods with different numbers of community members, ranging from 1 to 100,000.

  • iCL random fluctuations

    • Fluctuating iCL‾\overline{iCL}iCL: The average individual Commitment Level varies across periods to simulate changes in overall community commitment.

    • Changing iCLiCLiCL: Each member (M[1,2,3]M_{\tiny [1, 2, 3]}M[1,2,3]​) has a different individual commitment level, that keeps changing and being updated each period.

2. Fixed Parameters

  • 10 periods

  • 3 individual members ( M[1],M[2],M[3]M_{\tiny [1]}, M_{\tiny[ 2]}, M_{\tiny [3]}M[1]​,M[2]​,M[3]​ )

  • a stable performance ( P→=GCpECp\overrightarrow P = \frac {GCp}{ECp}P=ECpGCp​ ) set to a constant value of 1.05 (105%).

3. Parameters used

  • TCM (Total Community Members): The number of members in the community for each period.

  • iCL‾\overline{iCL}iCL (Average Individual Commitment Level): The average commitment level of all members in the community for each period.

  • iCL{iCL}iCL (Individual Commitment Level): The commitment level of each member, ranging from 1 to 10.

  • fiCLfiCLfiCL (Fractional Commitment Level): The fraction of the total commitment level attributed to each member.

  • TCP (Total Contribution Points): The total number of contribution points available in the community for each period.

  • ECp (Expected Contribution Points): The expected number of contribution points for each member based on their fiCL, calculated as ECp=fiCL⋅TCpECp = fiCL \cdot TCpECp=fiCL⋅TCp.

  • GCp (Given Contribution Points): The actual number of contribution points contributed by each member, calculated as GC=P→⋅ECGC = \overrightarrow P \cdot ECGC=P⋅EC.

  • PS (Participation Score): The cumulative participation score for each member, calculated as PSn=PSn−1⋅P→PS_n = PS_{n-1} \cdot \overrightarrow PPSn​=PSn−1​⋅P, with PS0=100PS_{\tiny 0} = 100PS0​=100.

4. Approximations for convenience

  1. TCP: The total contribution points available in each period. Here we constrained using the formula TCP≤TCM⋅100TCP \le TCM \cdot 100TCP≤TCM⋅100 "heavy tasks” worth 10 Contribution Points.

  2. PS: The participation score for each member. Calculated as PSn=PSn−1⋅P→PS_n = PS_{n-1} \cdot \overrightarrow PPSn​=PSn−1​⋅P, where PS0=100PS_{\tiny 0} = 100PS0​=100, to simulate cumulative growth based on consistent over-performance.

  3. iCL: The fraction of the total commitment level attributed to each member. Here calculated as fiCL=iCL×1TCM×iCL‾fiCL = iCL \times \displaystyle\frac {1}{TCM \times \overline{iCL}}fiCL=iCL×TCM×iCL1​ This way we’d set up one single average iCL ( iCL‾\overline {iCL}iCL) for the entire community, instead of generating millions of individual iCLs for each member.

5. Results

PreviousConclusions & Initial ApplicationsNextPS Playground

Last updated 10 months ago

⚽
Tab. 1 successfully shows that the PS of the three members grows steadily, without spikes, and without being influenced by the size of the community or the changes in iCL (as long as the P→\overrightarrow PP remains constant).