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Man and Machine > Task 5 > Flashcards

Task 5 Flashcards

1
Q

What is meant by cognitive science ?

A
  • understanding the processes that the brain uses to accomplish complex tasks
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2
Q

What are cognitive models ?

A
  • want to explain cognitive processes and how they interact,

- Trying to understand and conceptualize cognitive processes like categorization,

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3
Q

What are the 5 steps of cognitive modeling?

A
  1. Translate theoretical framework to a mathematical or computer language
  2. Add additional assumption (ad hoc assumptions)
  3. Estimate parameters
  4. Compare predictions with competing models
  5. Start over again
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4
Q

What differs cognitive models from other models ?

A
  • they derived from basic principles of cognition
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5
Q

Name two types of cognitive models:

A
  • prototype and example model of categorization
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6
Q

What is meant by the prototype model of categorization ?

A
  • Putting an object into a category based on prototypes (average object of each category)
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7
Q

What is meant by the exampler model of categorization ?

A
  • Putting an object into a category based on finding the matching part from ALL past remembered examples
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8
Q

What are the advantages of cognitive models over conceptual model?

A
  • since they use mathematical and computer language, they guranted produce only logically valid predictions
  • capable of precise prediction
  • Generalizeability = can make predictions that go beyond the original data
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9
Q

How can u translate a conceptual model into a cognitive model ?

A
  • via changing the verbal statement into mathematical or computational language
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10
Q

What is an example of a rule based system ? (comparison to deep learning)

A
  • SOAR modle
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11
Q

What is the main component of a rule based model ?

A
  • The production rule ->
  • If part -> Condition
  • Then part -> Action
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12
Q

What is meant by condition ?

A
  • specifies what must be true for a rule to apply

- Can be multiple factors

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13
Q

What is meant by action ?

A
  • specifies a set of things to do if the production applies

- can be multiple factors

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14
Q

What is the limitation of multiple “actions” and “conditions” ?

A
  • The multiple action can not be contradictory
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15
Q

What kind of knowledge can be presented in rules ?

A
  • General information about the world (non changable logical rules / bilogical /physics)
  • example would be language
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16
Q

What is the difference between logic and rule based system ?

A
  • rules do not have to be interpreted as universall true (rather as a default)
  • can better represent strategic information about what to do
  • logic based system focus on deduction regarding thinking
  • rule based system focus on SEARCH regarding thinking
  • rule based system have less representational power but more computational and psychological power in comparison to the logic system
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17
Q

What is meant by representational power ?

A
  • How much knowledge about the world can be represented?

- Or how to do things in the world

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18
Q

What is meant by computational power ?

A
  • How powerful and efficient are rule-based system

- How good is there Problem solving, planning, explanations, learning, language = useful

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19
Q

How does rule based problem solving work ?

A
  • They first search trough a problem space to find a path from current to goal state
  • In doing so people rely on heuristics bc it is impossible to search the entire space (to complex)
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20
Q

What is meant by problem space ?

A
  • is the space of possibilities that you must navigate trough
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21
Q

How do people search in the problem space ?

A
  • Serial processing (one rule at a time)

- parallel processing (multiple rules at a time)

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22
Q

Define planing:

A
  • Taking the best options out of the problem space and put them together
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23
Q

What kind of planing strategies do rule based model use ?

A
  • Backward and forward reasoning and bidirectional search
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24
Q

What is meant by backward reasoning ?

A
  • uses the logic of “which requires” -> starting from the goal and then going back
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25
Q

What is meant by forward reasoning ?

A
  • Uses modus ponens from current situation to -> goal situation
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26
Q

What is meant by bidirectional search ?

A
  • combines forward and backward reasoning
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27
Q

How do u learn according to a rule model ?

A
  • via applying rules over and over again
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28
Q

How do we build rules ?

A
  • Rules can be innate (from birth on)
  • Rules can be learned via inductive generalization
  • rules can be formed from other rules (via chunking and spezialization)
29
Q

What is a rule based system such as the SOAR capable of ?

A
  • can model high cognitive reasoning task
  • can model human learning processes
  • can copy human like behaviour in games
30
Q

Why is rule based system currently so well known ? In comparion to the formal logic system?

A
  • because it has the best psychological application -> Can account for many aspects of human behviour
  • And also it has a slight neurological plausability because there is a small analogy between rules and neurons connected by synapsed
31
Q

What is meant by the ACT-(R) system ?

A
  • The model states that complex cognition arises from an interaction between declarative and procedural memory.
  • Adaptive Control of Thought-Rational
32
Q

What does the R stands for ?

A

Rational analysis theory

33
Q

What is meant by rational analysis theory?

A
  • states that each component of the cognitive system is optimized with respect to demands from the environment
34
Q

What types of knowledge/memory does the ACT-R contain of ?

A

Declarative and procedural memory

35
Q

What is meant by declarative memory ?

A
  • Thinks we are aware of and can report on “we know “ (conscious)
  • facts that are represented in chunks
36
Q

What is meant by procedural memory ?

A
  • contains procedures (“how to do stuff”)

- instructions are represented in units called production rules

37
Q

How are declarative and procedural memory rleated ?

A
  • They are independent but interrelated via connections
38
Q

What type of connections relate declarative and procedural memory ?

A
  • The production rules (retrieval request)

- production compilation.

39
Q

What is meant by the production rule ?

A
  • production rules fire in procdeural memory and may require elements from declarative memory
  • A production rule is a: “If ->then” relationship
  • THIS PROCESS IS CALLED RETRIEVAL REQUEST
40
Q

What is meant by the production complementation ?

A
  • It is the creation of new production rules

- they get created in procedural memory from ‘chunks’ in declarative memory

41
Q

What are the key components of the ACT- R model ?

A
  • The goal stack
  • the current goal
  • procedural memory
  • declarative memory
  • production complementation
  • retrieval request
  • ACT-R takes its environment into account
42
Q

What is mant by the goal stack ?

A
  • Contains all goals which are currently not put on attention but are still needed to be asnwered (subgoal)
  • components:goals can be either “pushed” (Added) or “popped” (taken away) from current goal
  • Goals can only be pushed or popped in reverse order (last in = first out)
43
Q

What is meant by the current goal ?

A
  • represents what ACT-R is currently trying to do

atttention is on

44
Q

Explain declarative memory more in depth

A
  • it is a collection of chuncks

- 2 to 4 elements/slots per chunck

45
Q

What is meant by a chuck ?

A
  • A chuck consist of SLOTS a
  • First slot is called ISA which determines the type of the chunck (operator)
  • All chunks are not isolated but interconnected and spread activation via connections
  • Summary = each chunk has a level of activation and this activation tends to leak out and add to the activation of all the other chunks it is connected to.
46
Q

What happens when a chunck has lots of activtaion?

A
  • it will be easily found and retrieved from memory

- resemblance short-term memory

47
Q

What happens when a chunck has not that much activtaion?

A
  • it will be hard to find and may never be retrieved

- resemblance = long-term memory

48
Q

What happens when a chunck has no activation ?

A
  • it’ll be forgotten (at least temporarily until activation levels increase)
49
Q

What is so special about the activation lvl of a chunk ?

A
  • the activation lvl is not constant
  • the more it is used the more it increases, when it isn’t used, it slowly decreases
  • This allows to model a priming effect
50
Q

Explain procedural memory more in depth:

A
  • It stores procedures in form of production rules (multiple)
  • which have a condition and an action
51
Q

How does the procedural memory know which production rule is to choose?

A
  • whether its condition (the IF part) matches the current goal
  • whether the required chunks are in declarative memory.
52
Q

What do chucks and prodcution rules have in coman ?

A
  • They both have actvation
53
Q

What happens when a production rule has low activation ?

A
  • rule might not be used even though the conditions match the current state
54
Q

What happens when a production rule has lots of activation ?

A
  • the rule is more likely to be retrieved and used again in the future
55
Q

Name all four stages of the production compilation:

A
  1. Understanding instructions and examples (instructions represent = new knowledge)
  2. Production compilation: we try to solve problems by applying these instructions
  3. Practice: through practice we solve problems with increasing speed and accuracy)
    GOAL: First u have chunks in delcarative emory -> these chucks are turned into rules in procedural memory via practice (automatically response)-> rules create new chunks in declarative memory
56
Q

Explain in detail the second step of producing a new production rule ?

A
  • the declarative representation of instructions becomes transformed into a production rule
  • > Specific values are replaced by varaibles -> The rule becomes more general
57
Q

Explain in detail the third step of producing a new production rule:

A
  • Throug out practice the activation of the production rule and of the chuck increases
58
Q

What is a crtitic on the ACT- R model ?

A
  • it lacks psychological plausability bc the system does perfectly recall every subgoal on the goalstack and humans do not
59
Q

What example could we use to see how the ACT R works ?

A
  • word list memory task

- Presented with a list of items (one after another) and asked to recall them after some delay

60
Q

How can we compare a human with the ACTR model based on the list memory task ?

A
  • recall latency (i.e. time taken to recall an item)

- recall accuracy

61
Q

What were humans score on the list memory task ?

A
  • Primacy and recency effects (first and last elemnt showed highest accuracy )
  • Recall is slower for elements 1, 4 and 7 (due to the way items are chunked in memory)
62
Q

The ACTR is a hybrid model because:

A
  • it is connectionist: because in declarative memory graceful degradation
  • And rule based: because the pocedural memory allways needs rules
63
Q

How well did the model act in comparison to the human work regarding list memory ?

A
  • very similar to human
  • primacy and rencency effect was also present
  • Lattency was also similiar 1,4,7 It takes longer to recall something if u first have to switch the group
  • Limitation: Certain Parameters need to be set for differing types of recall
64
Q

What is meant by partial matching ?

A
  • a chuck can bes selected that only matches partially the item
  • happends: when chunck is highly active and a complete match is absent
65
Q

what is meant by default ?

A

it is a rough generalisations that admit exceptions

66
Q

What is meant by a production rule ?

A
  • rule based system

- IF -> then

67
Q

What if multiple conditions matches the current goal ? (how do we deide then which production rule we should use)?

A
  • Based on the activation lvl of the production rule !

- As allways high activation lvls are prefered

68
Q

Does the ACT (R) has a specific set of production rules?

A
  • The amount of production rule is not fixed

- The ACT (R) is able to learn new production rules

69
Q

Which approach is integreated in the ACT- R system ?

A
  • Goal directed approach
  • they take a current goal and a current state, and the system acts either to achieve the goal or add a new goal that needs to be completed first.

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