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There are still lots of things that are more easily answerable in games to see if they exist. For example, can we get AI to play deceptive strategies without b
by SpaceManNabs 6y ago
There are still lots of things that are more easily answerable in games to see if they exist.
For example, can we get AI to play deceptive strategies without being explicitly rewarded (Open AI hide and seek game, StarCraft fog of war plays, etc)?
As to whether it can translate to solving real world problems is arguable (there are some cases yes), but it definitely helps out in weeding inference models or training strategies that are not viable in games (and probably not the real world).
edit: Forgot to list an example. Using the same reinforcement learning strategies not to play games, but to design them.
- dontreact 6y agoThanks for the perspective. I have been asking this question for a few years now, and I think Deepmind's marketing has been pretty deceptive on this. What examples do you have in mind where the research from playing games with RL has carried over into solving a real-world problem? Probably the state of the art has advanced as I have focused in applying supervised learning on some applied problems that interest me.
- perl4ever 6y ago"can we get AI to play deceptive strategies without being explicitly rewarded" Haven't we seen quite a bit of that? I think there have been multiple items on HN about instances where ill-defined goals led to AI finding bugs in a simulation or unintended solutions. Deception is really just about human expectations.