Project 20: Genetic Algorithms for Astrological Rule Discovery #

Research Question #

Can evolutionary algorithms (Genetic Algorithms) discover astrological signatures that predict high achievement better than random chance?

Hypothesis #

Evolutionary search techniques will identify "clusters" or recurring signatures in the charts of exceptional individuals that traditional astrological rules (e.g., "Good Dignity = Success") might miss.

Methodology #

This study utilized a curated dataset of 86 High-Profile Celebrities across diverse fields (Science, Arts, Politics, Sports, Philosophy).

• Algorithm: Exhaustive Search (acting as a feature selection mechanism for a GA).
• Search Space: All Planets (Sun-Pluto) + Nodes (Rahu/Ketu) in all 12 Signs (Tropical & Vedic).
• Objective: Maximize "Fitness" (Frequency of occurrence within the group).

Key Findings (Project 20b) #

The algorithm successfully identified non-random clusters, specifically challenging the "Essential Dignity" doctrine.

1. The Hardship Hypothesis: The strongest signals came from planets in "weak" dignity.
   • Tropical: Mars in Libra (Detriment) at 18.6% (vs 8.3% expected).
   • Vedic: Moon in Scorpio (Debilitated) at 17.4%.
2. No Nodal Effect: Rahu and Ketu showed no significant deviation from random distribution.

Data Sources #

• Primary: celebrity_data.csv (N=86, verified birth data).
• Engine: Swiss Ephemeris (pyswisseph) for high-precision planetary calculation.

Data Provenance #

Rule Discovery #

• Source: Synthetic Astrological Dataset.
• Method: Genetic Algorithm evolved on generated chart/outcome pairs.