Author: John Tristan Ritland

Version: v0.3

a way to analyze the odds of a system giving a certain result. Because I don't have time to actualy teach myself statistics.

Okay, so I didn't realy know what I was doing when I started this, but as it turns out, there's a word for what I'm making: A Bayesian Network solver based off the Monte Carlo Method The node network is a Directed Acyclic Graph

I'm hoping to implement it using a boost graph library adjacency list. Function prototypes should be up soon. I switched to cmake for portability, and more importantly, because it (should) integrate better with the vim plugins I'm using, and can locate boost quickly and efficiently.

I should probably mention that this is a continuation of a college assignment, in which I did a similar thing, except with a highly specific case, which eliminated most of the difficulties innate in this one: A network of nodes with a certain probability of failure. It was implemented by an array to store the nodes (since I didn't understand pointers yet), and each iteration, the system would evaluate the nodes, to see if a input "1" made it through the network to the exit node, or if it failed along the way. This variant did support cycles, as with this specific problem, they would always converge to zero probability.

This program is Free Software: You can use, study share and improve it at your will. Specifically you can redistribute and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.