= 27d567bc2d48d9f40e9ccc20ea370b15)
TheOtherDave comments on The Power of Reinforcement - Less Wrong
You are viewing a comment permalink. View the original post to see all comments and the full post content.
= 783df68a0f980790206b9ea87794c5b6)
Loading…= b715d02e85f7b3b4ae65ca3d3e450868)
Subscribe to RSS Feed
Powered by Reddit
= f037147d6e6c911a85753b9abdedda8d)
You are viewing a comment permalink. View the original post to see all comments and the full post content.
Comments (467)
That's true and false. Intermittent reinforcement gets a more robust effect than continual reinforcement, yes, but randomly intermittent reinforcement isn't as effective as setting the reward threshold higher as the behavior becomes more common... e.g., rewarding only the 10% nicest things.
I want to design a reinforcement schedule in one of our apps. Can anyone link me to some specific guidelines on how to optimise this?
(Reinforce exactly what % of successes (30%? 26%? 8%?)? Reinforce performances in the top 10% of past performances (or the top 12%, or the top 8%?)? How does time factor (if the user hasn't used the app for a week, should I push a reinforcer forward?)?)
I can't, but if you find anything concise and useful, I'd love to hear about it myself.
My rule of thumb is to set the threshold so as to reinforce the top 20% or so of performances, and arrange performance frequencies so I'm reinforcing 2-3 times/minute during active training periods. But that's not based on anything.
I'll also note that reinforcing higher-tier performances more strongly works really well (though is hard to do consistently by hand), as do very intermittent "jackpots" (disproportional and unpredictable mega-rewards).