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## What is Opsmodelling

The Operation Modelling project is the software for "Math Methods In History" research direction. Mathematical methods are applied in many "parts" of history. One of the most important historical object types is war, and the most important and interesting part of war is battle. Usual historians analyse battles qualitatively. This approach gives no reliability. We are analysing battles with help of mathematics and it gives us much more reliable results.

There are many different mathematical approaches to description of battles. They depend on what type of battle is being described, what approximations are made and what we want to achieve. Our research is designated to battles with large quantities of units (See current mathematical paper for details). This dynamics of averages description gives well-known Lanchester equations in the simpliest case. This method can be used not only in history, but in physics(hydrodynamics, electrodynamics of plasma, etc), economics, etc -- for many problems with large amount of units(particles). Rigorous proof of this method can be done using theory of stochastic processes. I intend to do it in my next math paper.

There is another way of proving: conducting experiment. One of the main purposes of Opsmodelling is conducting such numerical experiment. This experiment consists of two parts:

1. solving approximate equations achived with our method of averages (numerical or presicious analitical -- the last one only for simple cases) This is intdiff subproject.
2. simulating the battle(under this I understand imitation of battle: each unit of fighting groups 'lives' on 2d surface of battle and attacks enemy units (how it is doing this, we are to define. See math doc for details). This is libbattle subproject.
After that we are to compare results of 1. and 2. and said something about presicions and boundaries of methods etc.

The other main goal of Opsmodelling is become an instrument for researching real historical battles (and we are to conduct such researches). Examples of non-presicious researches, using simplest models, can be found in appendixes of math paper. Having such powerful simulation software we'll be able to answer more complicated questions with high presicion.