Questions and CORRECT Answers
three levels of explanation - CORRECT ANSWER - functional, algorithmic, physical
functional level - CORRECT ANSWER - problem the capacity is supposed to solve
algorithmic level - CORRECT ANSWER - procedures that enable the problem to be
solved
physical level - CORRECT ANSWER - the neural/chemical substrates in which the
procedures are implemented
functional level of visual perception - CORRECT ANSWER - the inverse optics problem
algorithmic level of visual perception - CORRECT ANSWER - bayes' rule
functional level of language - CORRECT ANSWER - mapping from sounds to meanings
algorithmic level of language - CORRECT ANSWER - phrase structure trees
tacit knowledge - CORRECT ANSWER - things you "know" but cannot readily articulate
unconscious processing - CORRECT ANSWER - things your mind does without your
awareness
modularity - CORRECT ANSWER - functional specialization within the mind/brain
,innateness - CORRECT ANSWER - generally speaking, knowledge that is natural or
inborn; however, there is no exact consensus of how it is defined
rationality - CORRECT ANSWER - logic and reasoning, doing the right thing
heuristics and biases program - CORRECT ANSWER - holds that people are pretty bad at
logical reasoning, probability, and statistics; we make judgements using simplifying heuristics
heuristic - CORRECT ANSWER - a shortcut thinking strategy that often allows us to
make judgments and solve problems efficiently; usually speedier but also more error-prone than
algorithms
neuroeconomics program - CORRECT ANSWER - holds that the brain is outfitted with
sophisticated mechanisms for rapidly and accurately doing logical reasoning, probability, and
statistics
dual process models - CORRECT ANSWER - models of behavior that account for both
implicit: fast, automatic, effortless, and explicit: slow, controlled, effortful, processes
trolley problem - CORRECT ANSWER - a moral dilemma used to study moral decision
making; involves a speeding train headed towards five people that are on the track, and you have
the option of diverting the train to another track which only has one person on it; however, then
you are responsible
inverse optics problem - CORRECT ANSWER - P(H|data); for any 2D image, there's an
infinite number of 3D worlds consistent with that image; highly underdetermined inference
problem
inner picture theory of perception - CORRECT ANSWER - false theory suggesting that
perception works like a camera—what we end up with is a picture that is a straight up
representation of what is out there in the world; primary issue is that it fails to account for who is
doing the perceiving, and would end up in an infinite loop of perceivers within each others'
minds
, functions - CORRECT ANSWER - mappings from inputs to outputs
well-specified functional problem - CORRECT ANSWER - one-to-one mapping from
input to output; problem is easy to solve
not well-specified functional problem - CORRECT ANSWER - one-to-many mapping
from input to output; problem is very difficult to solve
perception - CORRECT ANSWER - the process of organizing and interpreting sensory
information, enabling us to recognize meaningful objects and events;
a multi-step, inferential process, and a function going from 2d retinal input to a 3d representation
of a scene
probabilistic inference - CORRECT ANSWER - the computation of posterior probabilities
for hypothesis given observed data; thoughtless process that shows how many ordinary
inferences involve hidden assumptions
perceptual inference problem - CORRECT ANSWER - the problem of inverse optics:
getting from the input (a 2d pattern of light on the retina) to the output (a 3d representation of
reality); can only be solved by relying on assumptions
how the mind works (steven pinker) - CORRECT ANSWER - argued that to solve the
problem of inverse optics, the brain supplies missing information through innate assumptions we
make about our surroundings
hidden assumptions for visual perception - CORRECT ANSWER - 1) there is a single
overhead light source
2) things that are in shadow are really lighter in color than what my sensors currently detect
3) things tend to move in a straight line (straight line)
4) all points on a moving object are assumed to move in synchrony (rigidity)