Geometric economics: multi-dimensional decision manifolds, A* pathfinding, and Bond Geodesic Equilibrium
Project description
eris-econ
Geometric economics: multi-dimensional decision manifolds, A* pathfinding, and Bond Geodesic Equilibrium.
Overview
Classical economics reduces human decisions to scalar utility maximization. This library implements the geometric economics framework from Bond (2026), which models economic decisions as pathfinding on a 9-dimensional decision manifold.
The core insight: Homo economicus is not wrong because humans are irrational — it's incomplete because it computes on a projected subspace of the actual decision manifold. Projecting from 9 dimensions to 1 (monetary utility) destroys information that is mathematically irrecoverable.
The Nine Dimensions
Every economic state is a point in R^9:
| Dim | Name | Examples |
|---|---|---|
| d₁ | Consequences | monetary cost, material outcome, expected value |
| d₂ | Rights | property rights, contractual obligations |
| d₃ | Fairness | distributional justice, reciprocity |
| d₄ | Autonomy | freedom of choice, voluntariness |
| d₅ | Privacy/Trust | information asymmetry, fiduciary duty |
| d₆ | Social Impact | externalities, reputation |
| d₇ | Virtue/Identity | self-image, moral identity |
| d₈ | Legitimacy | institutional trust, rule compliance |
| d₉ | Epistemic | information quality, confidence |
Dimensions d₁–d₄ are transferable (conserved in bilateral exchange). Dimensions d₅–d₉ are evaluative (not conserved, enabling mutual gains from trade).
Key Concepts
Bond Geodesic
The optimal path on the decision manifold from current state to goal, minimizing Mahalanobis distance + boundary penalties. This is computed via A* search, where:
- g(n) = accumulated cost (System 2: deliberate calculation)
- h(n) = heuristic estimate (System 1: moral intuition)
Bond Geodesic Equilibrium (BGE)
Generalization of Nash equilibrium to multi-dimensional manifolds. Each agent minimizes behavioral friction on their own decision complex. Reduces to Nash when all non-monetary dimensions vanish.
Emergent Behavioral Phenomena
These are not ad-hoc biases — they emerge geometrically:
- Loss aversion (λ ≈ 2.25): losses traverse more dimensions than gains
- Reference dependence: distance measured from current state on manifold
- Endowment effect: ownership activates rights + identity dimensions
- Framing effects: gauge transformations on the description basis
Installation
pip install eris-econ
Or for development:
git clone https://github.com/ahb-sjsu/eris-econ.git
cd eris-econ
pip install -e ".[dev]"
Quick Start
from eris_econ.games import ultimatum_game
from eris_econ.pathfinding import astar
# Build the proposer's decision complex
E = ultimatum_game(stake=10.0)
# Find the optimal offer (Bond Geodesic)
goals = {f"offer_{p}" for p in [0, 10, 20, 30, 40, 50]}
result = astar(E, "start", goals)
print(f"Optimal choice: {result.path[-1]}") # ~offer_40 (not offer_0!)
print(f"Total behavioral friction: {result.total_cost:.3f}")
from eris_econ.behavioral import compute_loss_aversion
import numpy as np
# Compute emergent loss aversion from metric structure
sigma = np.eye(9)
sigma[0, 6] = 0.3 # consequences-identity coupling
sigma[6, 0] = 0.3
lambda_ratio = compute_loss_aversion(sigma)
print(f"Loss aversion λ = {lambda_ratio:.2f}") # > 1.0
Modules
| Module | Description |
|---|---|
dimensions.py |
The 9 economic dimensions, transferable vs evaluative classification |
manifold.py |
Economic Decision Complex — weighted directed graph on R^9 |
metrics.py |
Mahalanobis distance, boundary penalties, edge weights |
pathfinding.py |
A* search for Bond Geodesic computation |
equilibrium.py |
Bond Geodesic Equilibrium via iterated best response |
games.py |
Standard games: ultimatum, dictator, prisoner's dilemma, public goods |
behavioral.py |
Loss aversion, reference dependence, endowment effect, framing |
calibration.py |
Parameter estimation for Σ and β from behavioral data |
welfare.py |
Multi-dimensional Pareto optimality and social welfare |
Citation
If you use this library in academic work, please cite:
@article{bond2026geometric,
title={Geometric Economics: Multi-Dimensional Decision Manifolds and Bond Geodesic Equilibrium},
author={Bond, Andrew H.},
journal={Journal of Economic Theory},
year={2026}
}
License
MIT
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