91–100 of 219 posts
Earlier quoted context omitted.
Main difference is all Dota heroes are viable in competitive. Also, there's no mirror match
Only 3 heroes not picked in TI, iirc. It hasn't always been this diverse though. This patch is particularly well balanced.
https://www.reddit.com/r/leagueoflegends/comments/4n5og5/com...
I wonder if this a good move for Valve. How many people will be loose interest from the game if next year OpenAI manages to pull off the 5v5 challenge, thus bringing DotA 2 to the same level as GO and chess for AI, i.e. beating the best human(s). Has there been any study on the popularity of chess after AI moved in? How about prize pools, as a large driving force of DotA 2 is the competitive scene? I suppose Valve wi…
Of course it's a good move. Millions watched AlphaGo, many of whom have never played Go before. Millions, almost every single gamer will watch AI vs Dota that will be amazing marketing for Valve.
In the interest of a "fairer" comparison, I wonder how much of a difference it would make to force the AI to simulate mouse/keyboard input and interpret the raw screen buffer output, rather than using direct APIs into the game's guts, to more faithfully emulate its human opponent. I'm guessing the peripheral inputs wouldn't be much of a hurdle, but the image processing step could be very interesting.
To be clear 1v1 mid lane is harder than 1 unit v 1 unit in sc. But it is at least 3 levels behind 5v5 human play. So first it's laining, which is showing in the game. Then is the ganking basically 2-3 player working together. Above that that's 5 men team fight. Then you have the strategy planning in the band pick phase, and in game movement coordination. There are other things like item choices, in game communication…
How does having a bot succeed cause appeal to be lost? First you're suggesting that the strategy will be "found" and never beaten (no room for improvement, not even in hero selection). Secondly.. Chess & Go have been around for thousands of years and they still are played en masse daily.
You might think not beating bots is OK. Not for me and many people have been involved in competitive scene. The moment machine beats human, a large part of the competition is gone. The essence is that you want to be the best. But if all you can do is to beat some other inferior opponents, what's the point?
> Secondly.. Chess & Go have been around for thousands of years and they still are played en masse daily.
This is irrelevant.
So an interesting thing you could do as a game company with an "unbeatable" bot is to use it to balance a metagame. Let the bots all play each other and tweak character stats etc until they win a proportional amount of the time. (This presupposes that the bot learns the game the way OpenAI claims it is, without needing to learn from player replays or from playing in a very different way than human players do with tre…
Games are mostly based on the skills of the players, so should games be balanced by assuming a human can do what a machine can? Of course not!
A bot can usually make computations way faster and more presice than humans.
Let's say a bot plays against another bot, both with different characters. One character might seem really overpowered compared to the other, but that might only be because the bots can react to certain events thousands of times faster than a human. Without that reaction time the tables might turn and the other character might be clearly stronger.
So how fast should we assume a human can do a given action? How precise should we assume the player is at fast calculations?
I do see a lot of things it can balance, but letting bots learn by themselves with no limitations will definitely not work out well.
this whole emphasis that openai and deepmind put on human/robot collaboration is a paper thin pr move in my opinion. the robots will be better than any human, humans will not be able to contribute a single thing soon. but they try to make us all feel safe by making it look like they benefit from our brains.
It will be interesting for deep learning, though, where the ideas are a bit more abstract. Perhaps humans will be useful for a while longer.
In the interest of a "fairer" comparison, I wonder how much of a difference it would make to force the AI to simulate mouse/keyboard input and interpret the raw screen buffer output, rather than using direct APIs into the game's guts, to more faithfully emulate its human opponent. I'm guessing the peripheral inputs wouldn't be much of a hurdle, but the image processing step could be very interesting.
How do you know it's not doing that already? I was under the assumption that open ai agents interacted with the environments through vnc.
OT: Is backdooring prevented by the game engine yet? Annoyed me that a useful tactic was "against the rules"
It's always been prevented in Dota 2. Buildings have backdoor protection, which makes them regenerate lost HP from recent attacks unless there are creeps nearby.
As a side note: I think the most impressive aspect of this AI is that it was trained without watching any human games. In contrast, AlphaGo was bootstrapped from a bunch of existing human games, which I imagine was crucial to its training. Being able to learn how to fake out the human player without having seen this action before is quite impressive.
Saw this live and as someone that's played Dota for many years, it's not as impressive as people make it out to be. A Shadowfiend 1v1 is primarily a test of mechanical skill and not judgment. A similar comparison is if a Counter-Strike or Quake bot would instantly snap to your head getting a headshot. Like, yeah, cool I guess, and it would beat 100% of human players 100% of the time, but it's not even remotely as imp…
What makes you think that? In the interview, they explicitly disclaim this.