In high-dimensional non-convex optimization, we have a way to describe algorithms found by a small amount of local optimization: “not even close to optimal.”
Does this extend to ‘a bunch of algorithms together’? (I.e. how does ‘the brain does not do everything with a single algorithm’ effect optimality?)
There’s no strong reason to think the brain does everything with a single algorithm.
Does this extend to ‘a bunch of algorithms together’? (I.e. how does ‘the brain does not do everything with a single algorithm’ effect optimality?)