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New AI Is Capable of Beating Humans At Doom (denofgeek.com)
An anonymous reader quotes a report from Den of Geek UK: Two students at Carnegie Mellon University have designed an artificial intelligence program that is capable of beating human players in a deathmatch game of 1993's Doom. Guillaume Lample and Devendra Singh Chaplot spent four months developing a program capable of playing first-person shooter games. The program made its debut at VizDoom (an AI competition that centered around the classic shooter) where it took second place despite the fact that their creation managed to beat human participants. That's not the impressive part about this program, however. No, what's really impressive is how the AI learns to play. The creator's full write-up on the program (which is available here) notes that their AI "allows developing bots that play the game using the screen buffer." What that means is that the program learns by interpreting what is happening on the screen as opposed to following a pre-set series of command instructions alone. In other words, this AI learns to play in exactly the same way a human player learns to play. This theory has been explored practically before, but Doom is arguably the most complicated game a program fueled by that concept has been able to succeed at. The AI's creators have already confirmed that they will be moving on to Quake, which will be a much more interesting test of this technologies capabilities given that Quake presents a much more complex 3D environment.
The point is that the AI learned to play the game from only screen data. No maps, no preset strategy, just visual data. So, it has to learn to recognize threats and obstacles, and what to do when it does.
Beating humans is a good test, because humans are good at exploiting patterns, so shortcuts like always taking a fixed route wouldn't work for long.
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In-game bots may be operating on a limited view, but they're operating on actual hard data in basically machine-usable form. What's impressive about this is that it learns from what's on the screen -- distances, obstacles, paths, its location are all learned from visual input.
What I'm curious about is how adaptable their visual learning system is or whether it's extremely Doom specific. I'd also be curious at how long it took to learn to play. I'd also be curious what the learning curve was -- linear, non-linear, flat, steep or what.