[salty_biscuits]

It's not like the research on games is at the expense of other more worthy goals. It is a well constrained problem that lets you understand the limitations of your method. Great for making progress. Alpha zero didn't just play chess well, it learned how to play chess well (and could generalize to other games). I'd forgive it 10000 times the resources for that.

[ttctciyf]

> It is a well constrained problem

But attacking not-well-constrained problems is what's needed to show real progress in AI these days, right?

[salty_biscuits]

I'd say getting better sample efficiency is a bigger deal. It isn't like POMDP's are a huge step away theoretically from MDP's. But if you attach one of these things to a robot, taking 10^7 samples to learn a policy is a deal breaker. So fine, please keep using games to research with.

[joshgel]

>it learned how to play chess well

This. Learning to play a game is one thing. Learning how to teach computers to learn a game is another thing. Yes chess programs have been good before, but that's missing the point a little bit. The novel bit is not that it can beat another computer, but how it learned how to do so.