COG 301 Midterm| Ques ons and answers | Updated
RATED A+ 2026
informa on process
the computa onal view of the mind
informa on processes as conten ul and purposeful
a quality of meaningfulness; informa on in the system as being about the world, as having
content, significant, or meaning; conten ul quali es some mes called seman c, or inten onal,
quali es
informa on processes as representa onal
a computa on must be represented in some way; further understanding of a computa on
requires an understanding of how the informa on is represented; representa onal schemes
that include rules for building complex symbolic structures out of simpler ones are called
combinatorial, genera ve, or produc ve
informa on processes as described formally
the computa onal view of the mind (informa on process) is understood so thoroughly that it
can be represented as an algorithm
algorithm
informa on processes defined in terms of syntac c structures of inputs and build syntac cally
structured outputs; the processes that operate on a representa on
cogni ve science as basic science
cogni ve science is universal; the concepts employed by cogni ve scien sts are in the pursuit of
basic scien fic knowledge; cogni ve scien sts seek to discover highly general and explanatory
fundamental principles of informa on processing
informa on processes understood at mul ple levels
The dis nc on between studying the competence of knowledge of a system and studying its
formal informa on processes can be thought of as a dis nc on between levels of analysis. The
formal analysis is at a lower level, providing an account of the informa on processes that
underlie the competence that is visible at a higher, behavioral level. The analysis of the seman c
,mapping from the formal representa ons to the domain can be thought of as a bridge between
the formal and knowledge levels. It explains why a formal system is a successful implementa on
of a par cular competence. Each level of analysis contributes its own insights to the overall
picture.
importance of computers to Cogni ve Science
A number of concepts and dis nc ons that are important in computer science are part of the
underlying assump ons of cogni ve science. More generally, the growth of computer science
has greatly accelerated the development of cogni ve science; the technique of expressing a
cogni ve theory as a computer program and then running the program to explore the
ramifica ons of the theory is now an important tool throughout cogni ve science
computa on (computability) to define what counts as an adequate explana on in psychology
the theory of computability was invented by logicians in the 1930s; provides a more powerful
no on of mechanism than was dreamt of by Descartes or Kelvin; shows how an elementary set
of building blocks can be used to construct an unlimited variety of complex symbolic processes;
these processes proved applicable to any domain; par cularly appropriate for modelling the
human brain
percep on
acquiring informa on
memory
storing, retaining, organizing, and retrieving informa on
reasoning
integra ng, applying, and extending informa on
language
communica ng expressing informa on
Marr's 3 Levels of Explana on
Computa onal (knowledge) level
Algorithmic level
Hardware (physical implementa on) level
computa onal (knowledge) level (Marr's explana on)
what is being computed: inputs, outputs, and constraints
, algorithmic level (Marr's explana on)
how it is computed, the specific formal process
hardware (physical implementa on) level (Marr's explana on)
what physical structures carry out those processes
computa onal input example
seeing soccer ball
computa onal output example
kicking soccer ball in desired direc on
computa onal constraints
some make the transfer from input to output easier
some make it harder
helpful computa onal constraints
situa on: all gradua ng seniors names removed from transcripts
goal: to reassign correct names to transcripts
input: all gradua ng seniors transcripts
constraint: all gradua ng seniors only have one major
unhelpful computa onal constraint
situa on: all gradua ng seniors names removed from transcripts
goal: to reassign correct names to transcripts
input: all gradua ng seniors transcripts
constraint: all gradua ng seniors have possibly more than one major
Marr's 3 Stages of Vision
Early vision
Middle vision
Late vision
early vision input
raw re nal image
early vision output
improved usable representa ons of re nal image
RATED A+ 2026
informa on process
the computa onal view of the mind
informa on processes as conten ul and purposeful
a quality of meaningfulness; informa on in the system as being about the world, as having
content, significant, or meaning; conten ul quali es some mes called seman c, or inten onal,
quali es
informa on processes as representa onal
a computa on must be represented in some way; further understanding of a computa on
requires an understanding of how the informa on is represented; representa onal schemes
that include rules for building complex symbolic structures out of simpler ones are called
combinatorial, genera ve, or produc ve
informa on processes as described formally
the computa onal view of the mind (informa on process) is understood so thoroughly that it
can be represented as an algorithm
algorithm
informa on processes defined in terms of syntac c structures of inputs and build syntac cally
structured outputs; the processes that operate on a representa on
cogni ve science as basic science
cogni ve science is universal; the concepts employed by cogni ve scien sts are in the pursuit of
basic scien fic knowledge; cogni ve scien sts seek to discover highly general and explanatory
fundamental principles of informa on processing
informa on processes understood at mul ple levels
The dis nc on between studying the competence of knowledge of a system and studying its
formal informa on processes can be thought of as a dis nc on between levels of analysis. The
formal analysis is at a lower level, providing an account of the informa on processes that
underlie the competence that is visible at a higher, behavioral level. The analysis of the seman c
,mapping from the formal representa ons to the domain can be thought of as a bridge between
the formal and knowledge levels. It explains why a formal system is a successful implementa on
of a par cular competence. Each level of analysis contributes its own insights to the overall
picture.
importance of computers to Cogni ve Science
A number of concepts and dis nc ons that are important in computer science are part of the
underlying assump ons of cogni ve science. More generally, the growth of computer science
has greatly accelerated the development of cogni ve science; the technique of expressing a
cogni ve theory as a computer program and then running the program to explore the
ramifica ons of the theory is now an important tool throughout cogni ve science
computa on (computability) to define what counts as an adequate explana on in psychology
the theory of computability was invented by logicians in the 1930s; provides a more powerful
no on of mechanism than was dreamt of by Descartes or Kelvin; shows how an elementary set
of building blocks can be used to construct an unlimited variety of complex symbolic processes;
these processes proved applicable to any domain; par cularly appropriate for modelling the
human brain
percep on
acquiring informa on
memory
storing, retaining, organizing, and retrieving informa on
reasoning
integra ng, applying, and extending informa on
language
communica ng expressing informa on
Marr's 3 Levels of Explana on
Computa onal (knowledge) level
Algorithmic level
Hardware (physical implementa on) level
computa onal (knowledge) level (Marr's explana on)
what is being computed: inputs, outputs, and constraints
, algorithmic level (Marr's explana on)
how it is computed, the specific formal process
hardware (physical implementa on) level (Marr's explana on)
what physical structures carry out those processes
computa onal input example
seeing soccer ball
computa onal output example
kicking soccer ball in desired direc on
computa onal constraints
some make the transfer from input to output easier
some make it harder
helpful computa onal constraints
situa on: all gradua ng seniors names removed from transcripts
goal: to reassign correct names to transcripts
input: all gradua ng seniors transcripts
constraint: all gradua ng seniors only have one major
unhelpful computa onal constraint
situa on: all gradua ng seniors names removed from transcripts
goal: to reassign correct names to transcripts
input: all gradua ng seniors transcripts
constraint: all gradua ng seniors have possibly more than one major
Marr's 3 Stages of Vision
Early vision
Middle vision
Late vision
early vision input
raw re nal image
early vision output
improved usable representa ons of re nal image
