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Sep 3, 2022 at 17:40 comment added Arnon Weinberg Interesting question. I think that intermittent (fixed or variable ratio) reward schedules are quite common in the industry, and once trained, subjects tolerate many unrewarded trials for sufficiently large occasional rewards. With a fixed ratio, subjects could do a block of trials before being rewarded (based on overall performance), while with a variable ratio, subjects would not know if not receiving a reward is due to failing a trial or just random chance. What do you think?
Sep 3, 2022 at 12:06 history edited J..y B..y CC BY-SA 4.0
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Sep 3, 2022 at 12:04 comment added J..y B..y And yes, sequential search in the parameter space is one way (which I followed when it combines with a pedagogical progression), but (as for a sequential search in a array of data points) it seems inefficient for monotonous abilities (i.e. where the parameter space is linear, and an availability is hold for a range of parameter values) where a binary search (if one did not mind giving arbitrarily hard challenges) would be much faster.
Sep 3, 2022 at 12:01 comment added J..y B..y I added some context. I am really looking for a general answer to the general question though!
Sep 3, 2022 at 12:00 history edited J..y B..y CC BY-SA 4.0
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Sep 3, 2022 at 7:41 comment added Arnon Weinberg I think this question could use some context ... ie, what is it that you are actually trying to do? For example, if you want to determine the maximum discrimination ability of some birds, then you can start with a quantity difference that all the subjects can manage, and gradually decrease the difference until each subject is no longer able to reliably discriminate.
Sep 2, 2022 at 14:03 history asked J..y B..y CC BY-SA 4.0