It would also be interesting to see if DeepMind challenges Dota 2 one day maybe. How they would handle a 5-man team game and adapting to major game updates?
I'm more of a LoL guy, but i'd be excited to see this in action. I think it's actually an easier challenge than starcraft - the action space is much smaller and dodging/aiming AI already gives some players extreme advantages (against the TOS of course).
IMO the smaller action space/better defined win conditions is outweighed by the greater playstyle diversity: SC has 3 races while League and Dota have 100+ champions to understand the interactions with. How is an AI supposed to know that Tryndamere's ult has a 0.5 second cast time, but can't be interrupted by any CC?
Personally, I think (all else being equal) Dota might be an easier starting point than League because of its focus on item abilities, rather than champion abilities. Anybody can use a BKB in Dota, but in League you have Fiora W, Morg E, and a bunch of other things. You have a smaller set of abilities/effects to worry about.
The dodge/aim AI can be situationally good (Cass bots) but still, the best players do win against scripters. Scripters rarely make it into the elite echelons of the ladder; there's a situation right now with a former pro Korean player who started scripting but couldn't make it back into Master tier. You'd expect a former pro with very in-depth game understanding to play at the very tip top level with some 'aim assist' but it doesn't appear to be the case!
This is incorrect as Starcraft has a much larger playstyle diversity than League. Every league game follows the same structure: with very high probability, one player will be top, one middle, and two bottom, with one jungler. Teams will farm with occasional gank attempts until the midgame, where there is a slow transition from farming to objective taking and teamfighting. This is relatively formulaic and easy to learn. In contrast, from the start of the game in starcraft, players can choose from a wide variety of strategies, ranging from early rush strategies (with low and high-tech variants), harass-and-expand strategies, greedy expand strategies, and safe expand strategies. Also, it must also construct a prior over strategies for its opponent that changes by map, as map properties change the viability of certain strategies.
Your example of script-users not attaining high ranking in online play for league of legends is also misguided. Because the action space in league is so much smaller than in starcraft, it is much easier to develop an AI with game strategy competency for league. Combine that AI with perfect mechanics, and human players should be falling very readily.
> Every league game follows the same structure: with very high probability, one player will be top, one middle, and two bottom, with one jungler.
The prevalence of lane swaps (2 go top, 1 goes bottom) in competitive is one major counterexample. In fact, these often turn into having 3 or 4 people in one lane at the start of the game, forcing a fast push strategy.
> Teams will farm with occasional gank attempts until the midgame, where there is a slow transition from farming to objective taking and teamfighting.
Stereotypical Chinese LoL matches are nearly all teamfights, for better or for worse. Regardless, laning and midgame is where I think you should consider my point of champion diversity as well. Here, mistakes can be more readily mechanically exploited (late game, mistakes are punished strategically), e.g. if a laner is far from baron without TP, exploiting a 5v4 fight is a strategic decision, whereas missing certain skills early on in certain matchups means a severely negative outcome if the opposite laner has the mechanics, e.g. no flash and Q on CD as Lux means any Morgana can flash ult for guaranteed kill. These have a bigger impact than racial considerations and probably make up for map considerations (idk)
The script user example is one of mechanics: top players still win against those with pixel perfect scripted mechanics. This is despite having some scripters having 'game strategy competency' (that might be a real thing, but I interpret it as a player having real game knowledge).
IMO the biggest challenge to a human player playing against a team of 5 AI-controlled players is that of communication; perfect understanding of each others' intent is a far cry from the communication of even practiced teams.
I like this idea. To be fair, You need five computers to communicate with each other. It will be a huge mark for ai if they can actually learn to communicate with effectively for achieving the goals. Vary the performance of each ai and allow them to swear at each other could get very interesting. I wonder if ai can emulate the toxic side of gamers......
Would be interesting on what level the communication can be done. Do you give them a predefined, limited, game-specific vocabulary and make do with that? Or can you have the networks "talk" in some random set of symbols, with a meaning they have established while learning?
I think it's pretty simple, you just take the starcraft AI, reduce the number of units it can handle at a time, maybe simplify its economy logic, and then let it go. Easy.
The interactions between individual unit types in a game like DOTA are much more complicated than, say, the interactions between marines, zerglings, and zealots; there are many more unit types, too.
as someone else pointed out, the interactions between the units are like fighting games. Computers already have the advantage at fighting games (like Streetfighter).
Micro and unit control is where the AI has the advantage.
The complexity of the unit interactions also has a strategic layer (drafting, lane assignment, timing) which may be far more difficult to train and isn't just purely the micro aspect of the problem.