Week 1 Doing Psych Flashcards

1
Q

2 main groups of methods

A

quan and qualitative

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2
Q

features of quan methods

A

development + test of specific theories
theories –> mathematical predictions can be tested by collecting data + stat analysis

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3
Q

features of qualitative

A

dev of verbal theories
open-ended/explanatory

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4
Q

what is a theory + specifications

A

principles that explain a system
specifies relations
explain existing + predict new data

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5
Q

what is NOT a theory

A

description
set of data
diagram

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6
Q

3 levels of analysis theory of mind

A

computational
representation and algorithm
physical implementation

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7
Q

2 main model types in psych

A

mathematical
process: symbolic, connectionist

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8
Q

computational theory

A
  • what problem is it solving (and why)?
  • constraints on its solution?
  • nature of the problem / the function being computed?
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9
Q

representation and algorithm

A
  • what info does the system represent + how
  • what it does with the info
  • what algorithm is used to extract useful info
  • what is the input to the system, what is its output + stages in between?
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10
Q

physical implementation

A

how are representations and algorithms realized in the hardware of the device itself
(e.g., in the neurons of the brain, the silicon of the computer, etc.)

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11
Q

what is a symbolic process model

A

represents knowledge as symbolic data structures
manipulate data with variable-ised rules

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12
Q

what is a connectionist process model

A

knowledge as nodes in a network
processing carried out by passing activation between nodes

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13
Q

what are representations of symbolic models

A

basic - atomic elements
rules - composing complex structure i.e. a language

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14
Q

what are processes of symbolic models

A

operations on data structures
applications of symbolic rules

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15
Q

what are production systems + how many components

A

prototypical symbolic model
3

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16
Q

3 components of production systems

A

base of known facts
set of inference rules
executive control structure

17
Q

5 stages involved in operation of production system

A

current state - known facts
state space - all possible states
goal state - state want the data base to be in
state transition - moving from one state to another
search - algorithm for traversing state space

18
Q

3 advantages of symbolic models

A

computational power
can define variablized rules
represent = reason

19
Q

5 disadvantages of symbolic models

A
  • rules too rigid for human behaviour
  • new representations = combos of existing ones
  • how are rules learned
  • no graceful degradation with damage
  • no obvious neural implementation
20
Q

what are connectionist models

A

models composed of networks of interconnected nodes

21
Q

what are nodes

A

simple processors that mimic neurons / populations of neurons

22
Q

what are connections in a connectionist model

A

weights between nodes

23
Q

what are representations in a connectionist model

A

patterns of activation on nodes

24
Q

what occurs during the processing of connectionist models

A

nodes pass activation over weighted connections
pos weights are excitatory connections

25
Q

advantages of connectionist models

A
  • flexible processing (parallel contraints)
  • flexible representations: distributed reps capture semantic content + permit auto generalization
  • graceful deg with damage
  • transparent neural implementation
26
Q

what are the disadvantages of connectionist models

A
  1. not symbolic
  2. ability to generalize depends on similarity of examples
  3. cannot represent/use variable-ised rules
  4. even children generalize to utterly dissimilar examples
27
Q

7 different vulnerable group categories

A

marginalized
socially excluded
limited opps
suffer abuse
hardship
prejudice
discrim

28
Q

8 vulnerable groups defined by SVG ACT 2006

A

lone parents
disabled
elderly
children
ethnic min
mentally ill
homeless
refugees