1/ Some bugs are fun to discover!
A short #phdlife story.
A few weeks back, I found a bug in my dissertation model. It was a misspecification of a learning rule -- literally, I forgot a minus sign. This was a good find in that it made things correct but it was otherwise boring.
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6/ Anyways, to sample over beliefs and stereotypes, I'm using stochastic acceptance, which has really nice properties for very dynamic distributions. https://jbn.github.io/fast_proportional_selection/ …
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7/ So, why did my model slow down drastically? Because that subtle fix from two weeks ago induced drastic (and predicted!) skews in the agent distributions.
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8/ The one that sunk performance was in the expectation distributions which are big (one per belief context) and determine activity selection. It went nearly power-law. The rejection rate skyrocketed!
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9/ I still don't have a decent fix. In fact, I was working on a paper for automatically balancing sampling (mixing strategies dynamically) in this scenario months ago before I shelved it for my dissertation work proper. But, it's kinda a neat a-ha!
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