| Yeah but humans can more easily make macro-decisions based on micro situations. It's easier for us to look at a map and figure out which side is winning, sometimes that's really hard for a computer to do. I'm not a Dota2 player, but like SC2 for example is a game with LOTS of room for AI improvements. I've always thought that having some sort of APM limit might actually encourage AI authors to adopt new and unique approaches to macro-strats, but it doesn't seem to be on the horizon. When it comes to do a small thing rapidly, I think bots are almost always going to win. When it comes to do something large-scale with finesse, I think humans are going to have an advantage for a LONG time. I think that part of what makes human agents so effective at certain tasks, especially in the context of being up against another human is that we can evaluate an event and better understand the WHY of it relative to the player that played it. If I see a player pull back a bit, sometimes I think to myself that maybe they saw something they weren't expecting or something they weren't quite sure how to handle. When a computer sees the same move, a floating point number among millions changes slightly. I can try and figure out why they might be pulling back, if I did something weird or if I did something totally normal I might suspect it is bait, etc. I can think all these things in a short period of time and while large AIs might have better FLOPS than me, it doesn't understand what I'm doing, why I do it, etc. Curriculum learning isn't as effective in bots as it is in humans is my contention, I guess. Fair/unfair is a pointless observation when it comes to humans vs bots. The diversity of human-based problem solving is the perfect friction to train AIs against, imo. |