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AI agents continue to rack up wins in the video game world. Last week, OpenAI's bots were playing Dota 2; this week, it's Quake III, with a team of researchers from Google's DeepMind subsidiary successfully training agents that can beat humans at a game of capture the flag.
As we've seen with previous examples of AI playing video games, the challenge here is training an agent that can navigate a complex 3D environment with imperfect information. DeepMind's researchers used a method of AI training that's also becoming standard: reinforcement learning, which is basically training by trial and error at a huge scale.
Agents are given no instructions on how to play the game, but simply compete against themselves until they work out the strategies needed to win. Usually this means one version of the AI agent playing against an identical clone. DeepMind gave extra depth to this formula by training a whole cohort of 30 agents to introduce a "diversity" of play styles. How many games does it take to train an AI this way? Nearly half a million, each lasting five minutes.
Source: https://www.theverge.com/2018/7/4/17533898/deepmind-ai-agent-video-game-quake-iii-capture-the-flag
(Score: 2) by PinkyGigglebrain on Tuesday July 10 2018, @05:34PM (1 child)
When one of these "AI" bots can get to level 70 in Final Fantasy XIV on it's own, from first quest to final boss, then I'll be impressed.
Till then it is nothing more than an classic aim bot with "AI" stuck into it's description.
"Beware those who would deny you Knowledge, For in their hearts they dream themselves your Master."
(Score: 0) by Anonymous Coward on Thursday July 12 2018, @05:41PM
Can dominate EVE Online without triggering the anti-bot mechanisms, then we will know AI Agents have reached the minimum acceptable level of capability.
Since very little in-game in EVE is bounded, it would make it a lot harder for such an AI to decide what is optimizable win/lose behavior and would require a much larger corpus of knowledge as well as submodels bounding different areas of interestm whether economic, combat, or specific sectors of space with unusual physics or gameplay features.
Once it is capable of learning all of that, becoming successful both economically and militarily, AND being able to intuit new changes to the game (like the new rift space or whatever it is called) without human intervention or hundreds to thousands of failures first, then it will be a leading world-class gaming AI.