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The point is that the brain is a kind of controller, and evolution does in fact select for the controllers fitness. The theorem asserts that the maximally effi

by bloaf 7y ago

The point is that the brain is a kind of controller, and evolution does in fact select for the controllers fitness. The theorem asserts that the maximally efficient controller is one which has an accurate model of the environment. That evolution hasn't produced a perfect controller isn't an argument against the point that evolution will select for brains with accurate models. So you're correct: environmental physics which have never been survival-relevant will have no selection pressure. But I think you are very incorrect to say that because our brain ignores the nose part of our eyesight that we have an inaccurate model. A model in process-control-speak means some kind of mathematical description, not the inputs to the controller.

mattkrause 7y ago
Evolution will select for brains with more accurate models subject to other constraints and as a result, I doubt it will rarely (if ever) reach a global maximum. More accurate models presumably have costs (e.g., bigger brains are metabolically expensive). The fitness landscape has local maxima, and they may be hard to move away from (as in the eyes I mentioned above). There are lots of caveats like those. We know that a lot of internal models are not particularly accurate. The visual system only acquires a tiny bit of high-resolution data at time (with a hole in it[0]) and interpolates the rest. Loss aversion, the gamblers' fallacy, and the rest suggest we're not great at modelling uncertain outcomes. Even mental models of physics differ from reality in some key ways [1]. It's possible that these are still slowly improving, but I think it's more likely that much better models have an unfavorable cost-benenfit profile. [0] The blind spot is different from the nose. There's a whole in your representation of the world, a few degrees away from the center of gaze. Your brain fills it in in surprising ways. Here's a fun demo that's a big hit with kids too: http://people.whitman.edu/~herbrawt/classes/110/blindspotdemo.pdf http://people.whitman.edu/~herbrawt/classes/110/blindspotdem... [1] Josh Tanenbaum's group has some cool studies looking at people's mental models of physics, which you may find interesting: https://www.pnas.org/content/110/45/18327.short https://www.pnas.org/content/110/45/18327.short

by bloaf 7y ago

mattkrause 7y ago

Evolution will select for brains with more accurate models subject to other constraints and as a result, I doubt it will rarely (if ever) reach a global maximum. More accurate models presumably have costs (e.g., bigger brains are metabolically expensive). The fitness landscape has local maxima, and they may be hard to move away from (as in the eyes I mentioned above). There are lots of caveats like those. We know that a lot of internal models are not particularly accurate. The visual system only acquires a tiny bit of high-resolution data at time (with a hole in it[0]) and interpolates the rest. Loss aversion, the gamblers' fallacy, and the rest suggest we're not great at modelling uncertain outcomes. Even mental models of physics differ from reality in some key ways [1]. It's possible that these are still slowly improving, but I think it's more likely that much better models have an unfavorable cost-benenfit profile. [0] The blind spot is different from the nose. There's a whole in your representation of the world, a few degrees away from the center of gaze. Your brain fills it in in surprising ways. Here's a fun demo that's a big hit with kids too: http://people.whitman.edu/~herbrawt/classes/110/blindspotdemo.pdf http://people.whitman.edu/~herbrawt/classes/110/blindspotdem... [1] Josh Tanenbaum's group has some cool studies looking at people's mental models of physics, which you may find interesting: https://www.pnas.org/content/110/45/18327.short https://www.pnas.org/content/110/45/18327.short