#Dota 2 super player mod
Valve’s Dota 2 - a follow-up to Defense of the Ancients (DotA), a community-created mod for Blizzard’s Warcraft III: Reign of Chaos - is what’s known as a multiplayer online battle arena, or MOBA. It’s a strong validation of what can be done with scaled up reinforcement learning, willingness to validate ideas in the real world, and a glimpse into what large scale AI deployments will be in the future.” How OpenAI tackled Dota 2 I’m deeply thrilled and humbled by the public reaction. “At the other end, our focus on the team had been to reach the highest levels of play at Dota 2 and hold our own against professional players, so it was a massive shift from our competitive mindset to the this world of investigation, external scrutiny, and robustness to Internet scale. On one end of the spectrum we are absolutely sitting at the edge of our seat awaiting some incredible strategy to unfold, a missed blind spot pop up, or witness meaningful cooperation between AI and humans,” said OpenAI Five team researcher Jonathan Raiman. “Arena was an immense source of anticipation and fear in the minds of many of us on the team. OpenAI says it plans to use the results to investigate to what extent OpenAI Five is making “macro-level decisions” versus relying on snap judgment and opportunistic plays. (Players spent an average of two and a half hours playing against it, and one person spent nearly 30 hours.) And it attracted quite an audience: The total number of Twitch users who viewed OpenAI Five Arena games totaled 486,000, and they watched streams for an average of 7 minutes.
Collectively, OpenAI Five played 10.7 years’ worth of game time facing human opponents - roughly the amount of data it generates every 12 minutes of training by self-play. Only 4 human teams were victorious in 2 games in a row against it and a measly 3 teams won 3 (one team won 10), and just 115 players with an average solo matchmaking rating of 6,500 (63% Immortal players with a rank of 500) beat the bot in competitive mode.
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