Hîsyêô Apostolic Collective Simulation (HACSim)

HACSim is an Agent-Based Model (ABM) of a participatory economy, simulating the "Annual Planning Procedure" of the Hîsyêô Apostolic Collective. It demonstrates how a decentralized, non-market economy can achieve allocative efficiency and social consensus through iterative democratic negotiation.

The simulation uses Mesa for the agent logic and Solara for the interactive web dashboard.

🚀 Features

• Participatory Planning: Simulates the negotiation between Worker Councils (Producers) and Primary Councils (Consumers/Residents) to agree on an annual production plan without markets or central planning.
• Iterative Price Discovery: Uses an "Iteration Facilitation Board" (IFB) to adjust indicative prices based on excess demand until convergence (Walrasian Tâtonnement).
• Ecological Limits: Sufferance Domains impose hard caps on pollution. Proposals that violate these caps are automatically vetoed.
• Governance & Consensus (Phase 4):
  • Inefficiency Purge: Industry Federations reject the least efficient producers if the industry is unprofitable.
  • Anti-Gridlock: Agents automatically switch to a "Compromise Mode" (force-closing gaps) if the plan fails to converge after a set number of iterations.
• Dynamic Economy Setup: Create custom Goods, Industries, Jobs, and Equipment recipes via the Dashboard.
• Data Persistence: Export and Import your economy configurations via JSON (supports Server-Side Load).

🛠️ Installation

1. Clone the repository.
2. Install dependencies:

   pip install -r requirements.txt

   (Requires: mesa, solara, pandas, scipy, matplotlib)

▶️ How to Run

Start the dashboard server:

solara run src/dashboard.py

Open your browser to the URL shown (usually http://localhost:8765).

📂 Project Structure

• src/dashboard.py: Main entry point. Defines the Solara UI and simulation loop.
• src/model.py: The HisyeoModel class container for the simulation ecosystem.
• src/agents/:
  • communicant.py: Consumer agents (maximize utility via Cobb-Douglas).
  • worker_council.py: Producer agents (maximize Social Benefit / Social Cost ratio).
  • primary_council.py: Aggregators for consumers.
  • ifb.py: The "Auctioneer" managing price adjustments and state transitions.
  • environment.py: Sufferance Domains handling pollution permits.
• src/ontology.py: Definitions for Good, Equipment, PollutionType.

⚙️ Configuration

The Dashboard allows you to tune critical parameters:

• Max Iterations: Hard limit for the planning loop.
• Closing Threshold: The iteration at which agents start "Compromising" to force convergence.
• Efficiency-Wage Cap: Limits income inequality based on labor onerousness.
• Sustenance Baseline: Basic income guarantee.

⚠️ Known Constraints

• Monopoly Prevention: Examples with fewer than 2 Worker Councils per Industry will fail to start (The industry federations do approvals because I am not sure how we would implement the proper worker council behavior for approving other production proposals).