Logo

MBCT Symposium - Shared screen with speaker view
Sia Ahmadi
02:00:58
Are you talking about “optimality” as it applies to a model or a decision?
Rosa Cao
02:17:58
A reminder to put your questions in the chat at any time. Students are especially encouraged to ask questions!
kalanit grill spector
02:21:45
I wonder about your approach using any sort of modeling approach to model these effects if you are interested in modeling neural mechanism; how important it for you to be neurally accurate?
m. chirimuuta
02:22:09
Do you think the behaviour would be optimal if it were not for constraints? Or do you not think that evolution pushes towards optimality in any case?
william newsome
02:23:13
Could Rachel please enlarge on the important (to me!) distinction between bayesian and heuristic models (quadratic, etc). I didn’t understand how the alternative models would work in the context of the attention task she laid out.
justin gardner
02:23:48
I wonder if you think about considering optimality in a terms of David Marr’s levels of abstraction - that optimality is about understanding the computational goals of the system, sub-optimality (or heuristics) as about the algorithms or implementational constrains.
Imran Thobani
02:27:46
I thought it was interesting that suboptimality can point us towards constraints on the system. But to what extent can we actually characterize these constraints, since it seems (to me) that in general, we don't know much about how information is encoded or how computations are implemented?
paul mazaika
02:29:43
Given your attention experiment, do you think the LPCD model can be extended to include resource constraints? Time is often a real world constraint on decisions.
luke
02:31:21
You noted an apparent conflict between the views of Stocker and Withagen et al. on whether evolution worked towards optimality, and as I understood it you said this apparent conflict was perhaps owing to using the term differently. Is that right, or is it possible that this was a substantive disagreement?