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    <p>There's a few questions embedded in there: -How to deal with large quantities of objects? If there is a constant number of fixed objects, you may be able to simply create an array of them, as long as you have sufficient memory. If you need to dynamically create and destroy them, you put yourself at risk for memory leaks without careful handling of destroyed objects. At a certain point, you may ask yourself whether it is better to use another application, such as a database, to store your objects, and perform just the logic in your C++ code. Databases will provide additional functionality that I will highlight.</p> <p>-How to find objects in a given distance from others. This is a classic problem for geographic information systems (GIS); it sounds like you are trying to operate a simple GIS to store your objects and your attributes, so it is applicable. It takes computation power to test SQRT((X-x)^2+(Y-y)^2), the distance formula, on every point. Instead, it is common to use a 'windowing function' to extract a square containing all the points you want, and then search within this to find points that lie specifically in a given radius. Some databases are optimized to perform a variety of GIS functions, including returning points within a given radius, or returning points within some other geometry like a polygon. Otherwise you'll have to program this functionality yourself.</p> <p>-Tree storage of objects. This can improve speed, but you will hit a tradeoff if the objects are constantly moving around, wherein the tree has to be restructured often. It all depends on how often things move versus how often you want to do calculations on them.</p> <p>-AI code. If you're trying to do AI on millions of objects, this may be your biggest use of performance, instead of the methodology used to store and search the objects. You're right in that simpler code for points farther away will increase performance, as will executing the logic less often for far away points. This is sometimes handled using Monte Carlo analysis, where the logic will be performed on a random subset of points during any given iteration, and you could have the probability of execution decrease as distance from the point of interest increases. </p>
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