All of Aleksi Pietikäinen's Comments + Replies

The unexpected difficulty of comparing AlphaStar to humans

This is not true. In Starcraft Broodwar there are lot's of bugs that players take advantage of but such bugs don't exist in Starcraft 2.

I think it's much more important to restrict the AI mechanically so that it has to succeed strategically that to have a fair fight. The whole conversation about fairness is misguided anyway. The point of APM limiter is to remove confounding factors and increase validity of our measurement, not to increase fairness.

1JohnBuridan2yHere to say the same thing. Say I want to discover better strategies in SC2 using AlphaStar, it's extremely important that Alphastar be employing some arbitrarily low human achievable level of athleticism. I was disappointed when the vs TLO videos came out that TLO thought he was playing against one agent AlphaStar. But in fact he played against five different agents which employed five different strategies, not a single agent which was adjusting and choosing among a broad range of strategies.
0Slider2yIn making of starcraft 2 there was the issue of what mechanics to carry over from sc1. If a mechanic that is kept is a ascended bug you off course provide a clean implementation so the new games mechanic is not a bug. But it still means that the mechanic was not put in the palette by a human even if a human decides to keep it for the next game. The complex strategy spaces are discovered and proven rather than built or designed. If the game doesn't play like it was designed but is not broken then it tends to not get fixed. In reverse if a designers balance doesn't result in a good meta in the wild the onus is on the designers to introduce a patch that actually results in a healthy meta and not make players play in a specific way to keep the game working.
The unexpected difficulty of comparing AlphaStar to humans

I think your feelings stem from you considering it to be enough If AS simply beats human players while APM whiners would like AS to learn all the aspect of Starcraft skill it can reasonably be expected to learn.

The agents on ladder don't scout much and can't react accordingly. They don't tech switch midgame and some of them get utterly confused in ways a human wouldn't. Game 11 agent vs MaNa couldn't figure out it could build 1 phoenix to kill the warp prism and chose to follow it with 3 oracles (units which cant shoot at flying units). The ladder agents d

... (read more)
The unexpected difficulty of comparing AlphaStar to humans

Sorry I worded that really poorly. Dumb and fast was a comment about relatively high-level human play. It is context dependend and as you said, the trade off is very hard to measure. It probably flips back and forth quite a bit if we'd slowly increase both and actually attempt to graph it. Point is, If we look at the early game, where both players have similar armies, unlimited athleticism quickly becomes unbeatable even with only moderate intelligence behind it.

The thing about measuring athleticism or intelligence separately is that we can measure athleti

... (read more)
1Richard Korzekwa 2yIt's all good; thanks for clarifying. I probably could have read more charitably. :) Yeah, I get what you're saying. To me, the quick recognition and anticipation feels more like athleticism anyway. We're impressed with athletes that can react quickly and anticipate their opponent's moves, but I'm not sure we think of them as "smart" while they're doing this. This is part of what I was trying to look at by measuring APM while in combat. But I think you're right that there is no sharp divide between "strategy" or being "smart" or "clever" and "speed" or being "fast" or "accurate".
4maximkazhenkov2yI think there are two perspectives to view the mechanical constraints put on AlphaStar: One is the "fairness" perspective, which is that the constraints should perfectly mirror that of a human player, be it effective APM, reaction time, camera control, clicking accuracy etc. This is the perspective held mostly by the gaming community, but it is difficult to implement in practice as shown by this post, requiring enormous analysis and calibration effort. The other is what I call the "aesthetics" perspective, which is that the constraints should be used to force the AI into a rich strategy space where its moves are gratifying to watch and interesting to analyze. The constraints can be very asymmetrical with respect to human constraints. In retrospect, I think the second one is what they should have gone with, because there is a single constraint could have achieved it: signal delay Think about it: what good would arbitrarily high APM and clicking accuracy amount to if the ping is 400-500ms? * It would naturally introduce uncertainties through imperfect predictions and bias towards longer-term thinking anywhere on the timescale from seconds to minutes * It would naturally move the agent into the complex strategy space that was purposefully designed into the game but got circumvented by exploiting certain edge cases like ungodly blink stalker micro * It avoids painstaking analysis of the multi-dimensional constraint-space by reducing it down to a single variable
The unexpected difficulty of comparing AlphaStar to humans

I don't think this was unexpected at all. As soon as Deepmind announced their Starcraft project, most of the discussion was about proper mechanical limitations since the real-time-aspect of RTS games favors mechanical execution so heavily. Being dumb and fast is simply more effective than smart and slow.

The skills that make a good human Stracraft player can broadly be divided into two categories: athleticism and intelligence. Much of the strategy in the game is build around the fact that players are playing with limited resources of athleticism (i.e.... (read more)

1Richard Korzekwa 2yBut it is unclear what the trade-off actually is here, and what it means to be "fast" or "smart". AI that is really dumb and really fast has been around for a while, but it hasn't been able to beat human experts in a full 1v1 match. The fact that strategy is developed under an athleticism constraint does not imply that we can't measure athleticism. What was unexpected (at least to me) is that, even with a full list of commands given by the players, it is hard to arrive at a reasonable value for just the speed component(s) of this constraint. It seems like this was expected, at least by some people. But most of the discussion that I saw about mechanical limitations seemed to suggest that we just need to turn the APM dial to the right number, add in some misclicking and reaction time, and call it a day. Most of the people involved in this discussion had greater expertise than I do in SCII or ML or both, so I took this pretty seriously. But it turns out you can't even get close to human-like interaction with the game without at least two or three parameters for speed alone.