One thing I've always found lacking in bot aiming algorithms is the concept of increasing accuracy over time. If a human has 1/3 of a second to aim at a target, the accuracy level will be fairly low. But allow 3 seconds of aiming, and most humans can consistently make headshots, unless the target is moving randomly. What I would regard as "human-like" is a system that has a dynamic jitter factor that logarithmically decreases to basically zero over a period of about 3 seconds or so (depending on skill level) if the bot is not moving or changing the angle it is facing (vertically or horizontally) more than a small amount. This can be fairly easily done by giving the jitter factor a half-life (no pun intended) of approximately 1 second. So if the max jitter factor is X, after 1 second it will be .5X, after 2 seconds it will be .25x, etc. If the bot starts moving, or turns more than say 30 degrees vertically or horizontally, then the jitter factor starts over at its maximum value and the bot has to restart the aiming process.

Currently Realbot (the bot I've had the most experience with lately) is very deadly at close range, but can be fairly easily sniped at long range, because the jitter factor in the aiming seems to be a constant based on skill level. (I'm basing this premise on watching bots in first-person view.) At close range, the bots get a lot of quick headshots, but at long range, they shoot around you and you can take your time and pick them off with a sniper rifle unless they connect with a lucky shot. This rewards bad tactics (standing still in the open for long periods of time engaging the enemy repeatedly) because you are no more likely to die standing still than you are if you move. Against humans, staying still in the open is a bad mistake, especially if engaging a sniper.