🕯️ Praxeology Engine (Rust)

"It is not the task of economics to announce what men ought to do, but what they actually do."
— Ludwig von Mises

📖 Overview

Praxeology Engine is an Agent-Based Modeling (ABM) simulation framework written in Rust, designed to explore the emergent properties of market processes from a micro-foundation of subjective value theory.

Unlike traditional macroeconomic models that rely on aggregate variables and equilibrium assumptions, this project simulates the economy from the bottom up. It instantiates individual Agents with subjective preferences, limited knowledge, and dynamic learning capabilities, allowing them to interact in a decentralized marketplace.

The goal is to computationally visualize key Austrian School concepts:

• The Subjective Theory of Value: Prices are not intrinsic but emerge from individual valuations.
• Price Discovery Process: How scattered knowledge coordinates through the price mechanism.
• Cantillon Effects: Simulating how monetary injection points distort relative price structures (Planned Phase).

🏗️ Architecture

The project leverages Rust's concurrency and safety features to simulate thousands of independent economic actors.

Core Components

• Product: Represents a good in the market. It does not have a "true price" but rather a probability distribution of how it is perceived by the population (Price & Elasticity distributions).
• Agent: An autonomous economic actor. Each agent:
  • Holds a unique Preference for each product (collapsed from the product's distribution).
  • Manages a Budget and makes decisions based on marginal utility (implied).
  • Learns from market history to adjust price expectations dynamically.
• Market: The arena where Agents meet. (Currently implementing decentralized matching logic).

Key Algorithms

1. Subjective Valuation Instantiation

Agents do not perceive the "average" price. Each Agent generates their own original_price and elasticity based on the Product's distribution, creating a heterogeneous landscape of demand.

2. Dynamic Expectation Adjustment (In Progress)

Agents adjust their bid/ask prices based on:

• Success Rate: The ratio of successful transactions in the last $N$ attempts.
• Elasticity: High elasticity agents are more sensitive to price changes and less likely to raise bids.

🚀 Getting Started

Prerequisites

• Rust (stable channel)