Simple Scaling Probability With Outliers in Python

I'm creating a virtual auction game, and I need more complex NPC behavior than I have now. Basically, every item has a base price (bp), and the starting bid (sb) for that item will be calculated with this range (or something very similar): 0.8bp <= sb <= 1.1bp. The opposing NPC bidders need to judge how reasonable the current bid is, compared to the base price and/or starting value, and, with some outlying behavior (i.e. betting when it seems a little irrational), bid reasonably on the current item. Put simply, it should bid aggressively on the item when the bid is lower or around the base price, and frugally bid on the item if it's high above the base price, or just give up.

The issue is, I really have no idea how to do this. Not only that, this is going to mainly be run on a TI-84 Plus CE calculator, so the external libraries and modules have to be pretty limited (essentially just random). It'd be great if you attach a brief (or long) explanation of any formulas/code you provide, because I'd love to learn more about this.