Synthese,
Journal Year:
2024,
Volume and Issue:
205(1)
Published: Dec. 20, 2024
We
defend
a
new,
neurocognitive
version
of
the
view
that
knowing
is
form
how
and
its
manifestation.
Specifically,
we
argue
P
to
represent
fact
P,
ground
such
representation
in
use
guide
action
with
respect
when
needed,
store
traces
representations,
exercising
relevant
know-how.
More
precisely,
agents
acquire
knowledge
via
their
systems
control
organisms
by
building
internal
models
environments
using
action.
Such
implicitly
things
are.
When
agents'
implicit
are
grounded
usable
for
guiding
have
P.
additional
capacity
manipulate
language,
they
also
explicitly
express
world
thus-and-so.
explicit
appropriately
Thus,
both
forms
Oxford University Press eBooks,
Journal Year:
2024,
Volume and Issue:
unknown, P. 87 - 116
Published: Aug. 9, 2024
Abstract
This
chapter
discusses
the
variety
of
ways
that
information
can
be
represented
in
order
to
support
planning,
prospection,
and
inference—here
referred
as
‘informational
models’.
It
outlines
several
types,
focusing
on
key
features
representational
structure
computational
process.
These
include
domain-specific
perceptual
reinforcement
learning
systems;
‘model-based’
systems
rely
representing
causal
structure;
structural
representations
cognitive
maps;
relational
reasoning
with
concepts;
using
one
relation
stand
for
another;
conceptual
models
domains
like
number,
natural
kinds,
causation.
The
informational
differ
along
various
dimensions:
organized
vs.
representation;
content-specific
content-general
computations;
local
non-local
inferences;
whether
inferences
are
automatic
or
deliberative;
model
itself
just
its
outputs
relied
deliberation.
diversity
raises
important
question
how
thought
integrate
such
heterogeneous
models—answered
next
chapter.
Oxford University Press eBooks,
Journal Year:
2024,
Volume and Issue:
unknown, P. 177 - 190
Published: Aug. 9, 2024
Abstract
This
chapter
examines
the
phenomenon
of
drawing
on
meaning:
transitions
between
mental
representations
seem
to
depend
or
draw
semantic
content
those
representations.
It
argues
that
there
are
two
distinct
ways
this
occurs.
First,
some
rely
only
logical
form
and
concepts
(content-general
transitions).
Second,
content-specific
specific,
non-logical
involved,
demonstrating
an
understanding
grasp
their
meaning.
For
example,
inferring
a
dog
barks
by
direct-CS
inference
relies
meaning
barking.
The
defends
elaborates
distinction
its
implications.
Representing
information
explicitly
can
enable
content-general
less
directly
content.
Oxford University Press eBooks,
Journal Year:
2024,
Volume and Issue:
unknown, P. 27 - 58
Published: Aug. 9, 2024
Abstract
This
chapter
examines
semantically-significant
representational
structure
and
distinguishes
two
broad
kinds:
structural
representation
general-purpose
compositional
structure.
Structural
representations
rely
on
a
correspondence
between
world,
like
maps.
General-purpose
is
exemplified
by
natural
language
sentences
conscious
deliberate
thoughts
composed
out
of
concepts.
allows
any
concept
to
be
combined
with
other
concept(s)
the
right
type,
unlike
where
relations
that
define
have
specific
contents.
After
defining
structure,
surveys
different
varieties
found
in
mental
representations.
It
then
characterizes
representation,
distinguishing
this
from
mere
organization.
Next
it
focuses
compositionality
thought,
arguing
not
form
or
if
is,
only
very
abstract
kind.
The
clarifies
terminology
draws
connections
computational
processes,
informational
models.
Oxford University Press eBooks,
Journal Year:
2024,
Volume and Issue:
unknown, P. 191 - 210
Published: Aug. 9, 2024
Abstract
This
chapter
argues
that
deliberative,
concept-driven
thinking
incorporates
metacognitive
monitoring
and
control.
First,
thinkers
have
an
appreciation
of
the
reliability
concepts
for
categorization
inference.
Second,
conclusions
reached
through
inference
elicit
epistemic
feeling
rightness
reflects
plausibility
conclusion.
Inference
patterns
themselves
likely
attract
feelings
constitute
a
phenomenological
guide
thinker.
Third,
integrated
collection
representations
constructed
in
‘cognitive
playground’
during
deliberation
is
plausibly
monitored
coherence,
affecting
thinker’s
confidence.
Together,
these
forms
appraisal
enable
thinker
to
appreciate
what
going
on
concept-involving
thinking.
part
makes
cognitive
process
attributable
person.
The
elaborates
this
idea
shows
how
it
supported
by
philosophical
arguments
psychological
evidence.
Oxford University Press eBooks,
Journal Year:
2024,
Volume and Issue:
unknown, P. 59 - 86
Published: Aug. 9, 2024
Abstract
This
chapter
draws
a
distinction
between
two
types
of
computational
process
that
mental
representations
can
enter
into.
Content-specific
transitions
are
faithful
to
representational
content
due
the
specific
non-logical
concepts
involved.
Content-general
transitions,
e.g.
deductive
inferences,
depend
only
on
broadly-logical
in
order
be
content.
Structural
representations,
which
rely
special-purpose
compositional
principles,
tend
into
content-specific
computations
rather
than
inferences.
Conceptual
relying
as
they
do
general-purpose
compositionality,
well
suited
for
content-general
computations.
However,
also
participate
transitions.
The
argues
and
processes
need
integrated
explain
concept-driven
thinking.
former
capture
based
pattern
recognition
statistical
structure,
while
latter
underpin
logical
An
account
thinking
needs
incorporate
both
inferences
involving
concepts.
Cognitive Neuroscience,
Journal Year:
2024,
Volume and Issue:
15(3-4), P. 119 - 121
Published: Sept. 21, 2024
I
argue
that
ideas
and
models
about
the
mechanisms
of
neural
computation
representation
-
including
computational
architecture,
representational
format,
encoding
schemes,
learning
methods,
computation-representation
coordination,
substrate-dependent
aspects
must
be
tested
by
studying
embodied
systems.
Thus,
cognitive
neuroscience
study
computations
over
representations
an
research
program.
Synthese,
Journal Year:
2024,
Volume and Issue:
205(1)
Published: Dec. 20, 2024
We
defend
a
new,
neurocognitive
version
of
the
view
that
knowing
is
form
how
and
its
manifestation.
Specifically,
we
argue
P
to
represent
fact
P,
ground
such
representation
in
use
guide
action
with
respect
when
needed,
store
traces
representations,
exercising
relevant
know-how.
More
precisely,
agents
acquire
knowledge
via
their
systems
control
organisms
by
building
internal
models
environments
using
action.
Such
implicitly
things
are.
When
agents'
implicit
are
grounded
usable
for
guiding
have
P.
additional
capacity
manipulate
language,
they
also
explicitly
express
world
thus-and-so.
explicit
appropriately
Thus,
both
forms
