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Monte Carlo Engine Agent

Uses NumPy/SciPy for high-performance Monte Carlo simulation. Runs 10,000+ iterations with three-point duration estimates, generates probability distributions for milestone completion, calculates P10/P50/P90 completion dates, and identifies activities with highest schedule sensitivity.

Agent ID
monte-carlo-engine
Sector Government, Healthcare, and Education Infrastructure
Status
Operational

Problem Statement

The challenge addressed

Deterministic schedules provide false precision. Project teams need probabilistic forecasts that account for uncertainty in activity durations.

Core Logic

How the agent solves it

Uses NumPy/SciPy for high-performance Monte Carlo simulation. Runs 10,000+ iterations with three-point duration estimates, generates probability distributions for milestone completion, calculates P10/...

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