A Status and BlockScience Collaboration

Economic Model Research, Simulation, and Testing

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Educational Digests

The following documents constitute two of a planned four “walkthrough” digests of the Status peer-to-peer (p2p) network’s implementation in cadCAD. The first digest commences with a detailed overview of the architecture of the network, covering the participants, p2p structure, system goals and its concomitant design. The second digest covers a behavioral model of reputation and trust between p2p members, using research in collective decision-making and emergent cooperation along with random auditing as an incentive mechanism. The third digest (in progress) casts the network as a generalized dynamical system (GDS), which provides a mapping from the system and its architecture to its implementation in the cadCAD framework for simulation. The fourth digest will indicate future steps, both to expand cadCAD’s use as a simulation and testing tool and to demonstrate the possibility of leveraging cadCAD’s modularity to implement a Decision Support System for running networks, as a “Digital Twin”.

Architecture Digest

Contextual hierarchy of the STATUS network as a cryptoeconomic system.

Cooperative Behavior Digest

Incentive Mechanism underlying the p2p network.

Generalized Dynamical System Digest

The STATUS network composed as a Generalized Dynamical System and framed in a cadCAD Specification.

Decision Support System Digest

The framework for the cadCAD model to serve as a Decision Support System for the STATUS network utilizing the parameter selection under uncertainty workflow.

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Models and Tests

Implementing the above architecture and design decisions into models reside in branches in this repository.

Validation Model

Network Routing Model validating networkx objects as class within simulation for retaining activity and dynamic local connectivity information.

Overlay Network Model

Building off the validation model, adding Kademlia Ping and Store RPC methods for maintaining node neighborhood activity and liveness logs.

Online Learning Incentive Model

An online learning incentive model provides sudsidies and charges penalties for incentivizing faster routing. A series of experiments explores the parametric tuning of the classifier as well as the amount of message payment subject to penalty and available for subsidy.

Payment Distribution Testing

Experiments allocating payment percentages for proscribed tasks necessary for message routing and message storage. Both sets of parametric tests explore the economic fabric of the network as nodes take on blended tasks to operate the network through the concept of personas.

Escrow Relaxation

Moving away from necessitating escrowed payment prior to message initiation to allow for cooperative behavior in a decentralized manner.

Simulations and tests were performed using cadCAD.

To explore for yourself, you must install Python 3 and our Python package cadCAD .

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by BlockScience
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cadCAD is a Python package that assists in the processes of designing, testing and validating complex systems through simulation, with support for Monte Carlo methods, A/B testing and parameter sweeping.

Getting Started with cadCAD

0. Pre-installation Virtual Environments with venv (Optional):

If you wish to create an easy to use virtual environment to install cadCAD inside of, please use the built in venv package.

Create a virtual environment:

$ python3 -m venv ~/cadcad

Activate an existing virtual environment:

$ source ~/cadcad/bin/activate
(cadcad) $

Deactivate virtual environment:

(cadcad) $ deactivate
$

1. Installation:

Requires >= Python 3.6

Option A: Install Using pip

$ pip3 install cadCAD

Option B: Build From Source

$ pip3 install -r requirements.txt
$ python3 setup.py sdist bdist_wheel
$ pip3 install dist/*.whl

Option C: Using Nix

1. Run curl -L https://nixos.org/nix/install | sh or install Nix via system package manager
2. Run nix-shell to enter into a development environment, nix-build to build project from source, and nix-env -if default.nix to install

The above steps will enter you into a Nix development environment, with all package requirements for development of and with cadCAD.

This works with just about all Unix systems as well as MacOS, for pure reproducible builds that don't affect your local environment.

2. Documentation:

• Simulation Configuration
• Simulation Execution
• Policy Aggregation
• Parameter Sweep
• Display System Model Configurations

3. Connect:

Find other cadCAD users at our Discourse. We are a small but rapidly growing community.

4. Contribute!

5. Install Dependent Data Science Libraries

   $ pip3 install numpy
   $ pip3 install pandas
   $ pip3 install networkx
   $ pip3 install scipy
   $ pip3 install matplotlib
   $ pip3 install seaborn