| > This is just not true. Do you know the game? Are you speaking as a player? Or are you telling us what's written in the OpenAI blog post? There is nothing a player couldn't figure out. The caster team lost because of the broken game and because few of them were rusted (Merlini hadn't played for months). The bots were garbage at the TI, and got beaten without any problem by the pro teams. A former player. I'm not regurgitating the blog post, I'm regurgitating what the players themselves said. The AI got beaten by pro teams (top <<1%), but the matches were competitive in the early game, and only later did the bots run into trouble. To give a couple of specific examples of novel behavior, the AI figured out a solid deathball strategy and was able to exploit that to beat a lot of teams, it liberally used fortify to protect creeps and sustain pushes, and it was way more aggressive in rotating its supports to critical lanes in the early game. Now, no single one of those things is entirely novel, but the combination of all of them (especially by a machine that learned it on its own) is what is novel, and what allowed the strategy to be successful. > The hero pool is still 18 heroes. Dota 2 has over 110 heroes. Can you please try to think what makes you say something so wrong with so much confidence? Admittedly this was a mistake, the language they used in their blog post was "Removed our last major restriction from what most pros consider 'Real Dota” gameplay'", which is poorly explained and made me think the hero pool was entirely open. DotA is basically 2 games, the drafting part and the gameplay part. The bots made huge progress in figuring out the gameplay part, which is super impressive. >> Casters don't count as serious players. Maybe we're using different language. The casters are definitely in the top 1% of players, or more, which I consider "serious", but not "the best". But no one was arguing that the bots are "the best", which is self-evident from their loss at the International. Anyways, this is all beside the point. What OpenAI was able to do was really impressive and is only helping to advance the state of reinforcement learning. You argued that there's nothing impressive about what they've done, but I'd love to see you point me to an example of an ML algorithm that learned to play a team game as complex as DotA at a competent level. |
> is only helping to advance the state of reinforcement learning
Zero new algorithms or ideas were introduced by OpenAI Five. We just learn that model-free RL doesn't scale and we already knew that from Atari and robotics benchmarks.