51–60 of 79 posts
Point this thing at the stock market and see how that game plays out.
Is there a way to learn Go from scratch using these AIs? I wonder if it would pay off in the long run to be fully trained by one.
I think the strength or lack thereof of your opponent is actually much less important than the strength of the AI you use to review your games. After each game you should study the AI's advice and learn the moves it recommends.
Would it be able to play(and win) Among Us as an imposter or we are still far away from that?
The full Atari game list (Appendix I) is interesting. It's not better at every game, and scores a zero on Pitfall and Montezuma's Revenge.
As impractical as the idea is, reinforcement learning is so damn fun. I highly recommend others to play around with it. I originally was using the famous fork of OpenAi baseline, stable baseline but had issues with tuning with Optuna. I recently stumbled across Ray from Berkley [1] and it has a newer and fancier built-in hyper-parameter tuner. Even as a hardware engineer that's only a software hobbyist can make the c…
Eh, I'd say it's fun if you have a couple thousand TPUs lying around. If you're just messing around with 1 GPU and a desktop PC you should be happy to get Atari breakout to work.
Point this thing at the stock market and see how that game plays out.
Point this thing at the stock market and see how that game plays out.
It's not so clear to me how you would train a reinforcement learning agent for the stock market. You have historic data for prices etc. But that's more of a supervised learning thing. You could set it loose on one of those realtime market simulators, but the agents actions wouldn't have any impact on the simulation right?
Whoa, this is extremely impressive. Quotes from the BBC article: > "For the first time, we actually have a system which is able to build its own understanding of how the world works, and use that understanding to do this kind of sophisticated look-ahead planning that you've previously seen for games like chess. > "[It] can start from nothing, and just through trial and error both discover the rules of the world and u…
I've noticed all the top performing AI reinforcement algorithms i hear about know next to nothing about the initial rules. And not only do they perform as well as more supervised methods, but much better The one exception is self driving. I listened to the Lex Fridman interview with ceo of waymo recently and he made a case for the controlled environment (e.g. separate detection from decision making and planning) and…
It would also give the gaming industry a kick in the pants to start making better AIs.