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Modeling Speed-Accuracy Tradeoffs in Recognition. Darryl W. Schneider John R. Anderson Carnegie Mellon University. Modeling Behavioral Data With ACT-R. Mean RT and Error Rate. Speed-Accuracy Tradeoff Functions. Correct and Error RT Distributions. Speed-Accuracy Tradeoffs.

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Modeling speed accuracy tradeoffs in recognition

Modeling Speed-Accuracy Tradeoffs in Recognition

Darryl W. Schneider

John R. Anderson

Carnegie Mellon University


Modeling behavioral data with act r
Modeling Behavioral Data With ACT-R

Mean RT and Error Rate

Speed-Accuracy Tradeoff Functions

Correct and Error RT Distributions


Speed accuracy tradeoffs
Speed-Accuracy Tradeoffs

People can trade speed for accuracy when performing a task

Speed-accuracy tradeoff functions can be measured using the response signal procedure

  • Typically involves a choice task (e.g., recognition)

  • A stimulus is followed at a variable lag by a signal to respond immediately (e.g., yes/no response as to whether the stimulus was studied)

  • Examine accuracy as a function of lag


Speed accuracy tradeoff function
Speed-Accuracy Tradeoff Function

Asymptote (λ)

Rate (β)

Shifted exponential function:

Intercept (δ)

Chance



Act r model long lag
ACT-R Model: Long Lag

Response signal

Stimulus onset

Response

Signal encoding

Response execution

Stimulus encoding

Memory

retrieval

(wait)

Lag

Time available for retrieval

Trial time


Act r model short lag
ACT-R Model: Short Lag

Stimulus onset

Response signal

Stimulus encoding

Memory

retrieval

Response

Signal encoding

Guess

Response execution

Lag

Time available for retrieval

Trial time


Modeling the speed accuracy tradeoff
Modeling the Speed-Accuracy Tradeoff

Accuracy depends on the probability that retrieval finishes in the time available

  • If retrieval finishes, accuracy is perfect

  • If retrieval does not finish, accuracy is lowered due to guessing

    Retrieval time

  • Calculated with the standard ACT-R equations

  • Activation noise produces a time distribution


Modeling the speed accuracy tradeoff1
Modeling the Speed-Accuracy Tradeoff

Probability that retrieval finishes in time:

Time available:

  • External deadline (lag)

  • Internal deadline (failure time)

  • Shorter deadline determines the time available


Modeling fan effects on sat functions
Modeling Fan Effects on SAT Functions

Fan effect: It takes longer to recognize an item as its associative fan increases

  • Associative fan = number of associations with other items in memory

    ACT-R can already model the fan effect

  • As fan increases, associative activation from the probe to items in memory decreases, resulting in memory retrieval taking longer


Experiments
Experiments

Our Experiment

  • Person-location pairs

  • Well-learned

  • Fan 1 vs. Fan 2

  • Associative recognition: targets vs. rearranged foils

  • Response signal procedure with 8 lags

Wickelgren & Corbett (1977)

  • Word pairs and triples

  • Briefly studied

  • Fan 1 vs. Fan 2

  • Associative recognition: targets vs. rearranged foils

  • Response signal procedure with 8 lags


Modeling fan effects on sat functions1
Modeling Fan Effects on SAT Functions

Our Experiment

Well-learned materials

Wickelgren & Corbett (1977)

Briefly studied materials

Internal deadline shorter than external deadline

Internal deadline longer than external deadline


Take home message
Take-Home Message

ACT-R can model speed-accuracy tradeoffs in response signal data


Current directions
Current Directions

Modeling nonmonotonic speed-accuracy tradeoff functions

  • Different types of information are retrieved in series and inform the guessing process

    Modeling reaction time distributions

  • Free-response procedure

  • Guessing is probabilistic and occurs in parallel with retrieval


For more information
For More Information

Schneider, D. W., & Anderson, J. R. (2012). Modeling fan effects on the time course of associative recognition. Cognitive Psychology, 64, 127-160.

Available on the ACT-R website


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