Decision Speed Optimisation

I was playing around with a speed comparison with manual point-in-field checks to the Rectangle2D.Double.contains(x,y) method, and discovered that if I used && between the booleans I got pretty much exactly the same speed, but if I use & I get double the speed and exactly the same result. I'm guessing this is due to my CPU being able to evaluate multiple boolean expressions simultaneously, but if && is used only one is allowed to be executed at a time, or perhaps & just allows the pipelines to stay more full because there is less branching.

Of course, there are some reasons you might want && instead, like null checking before examining an object property, and && is smaller codesize for those bots that are codesize restricted, but particularly for high-load situations like the inside of precise prediction or play-it-forward loops, using & for your decisions might gain you some speed =)

Nice. This is a kind of optimization that you can't figure out by doing CPU profiling alone.

I'm actually implementing a rotated Rectangle2D.Double so that I can evaluate out-of-bounds PIF with a projected replay in Neuromancer. I was worried that it would be much slower than a standard .contains(x,y) function, so I was testing that. When I hit on the bitwise operations I thought I'd try a standard non-rotated function, and it was twice as fast as the awt.geom one. My rotated function is now slightly faster than the awt.geom as well.

I agree that sprinkling them around liberally isn't really going to make much of a difference, and will affect readability, but for something where you just have a bunch of numerical comparisons and the costs for all the branches will be more expensive than any saved time from the short-circuit provided in &&, this could be a decent speedup. The only real applications in RoboCode that would be intensive enough and have enough decisions to make this worthwhile, at least that I can think of, are in-field-bounds testing and range searches in Kd-Trees.