Behavioral models quiz
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Questions and Answers

Models inherently improve statistics, over the use of statistics on direct measurements

False

Only data-driven, and not generative models, can be fit to data

False

Models provide stricter opportunities for testing our theories as opposed to worded theories

True

A model can serve to summarize data into a focused set of parameters for further interpretation/comparison/testing

<p>True</p> Signup and view all the answers

All models are wrong, but some models are useful

<p>True</p> Signup and view all the answers

Avoiding overfitting. Which of the following statements on fitting are true? Select one or multiple correct answers.

<p>When countering overfitting on a train set, one can use parameter penalisation such as Information Criteria.</p> Signup and view all the answers

Reinforcement Learning. The Rescorla-Wagner model is a simple model that explains many aspects of learning. Which of the following aspects of a classical conditioning process can be accurately modeled using a Rescorla-Wagner model? (single correct answer)

<p>Extinction, “Kamin Blocking”, Exponential nature of learning with fixed time constant, How all learning asymptotes to the value of feedback</p> Signup and view all the answers

Reinforcement Learning. What ingredient of the Rescorla-Wagner model causes/explains extinction?

<p>Having a non-zero expectation of value causes negative prediction errors on zero feedback, which in turn cause negative value updates.</p> Signup and view all the answers

Study Notes

Models and Statistics

  • Models enhance the effectiveness of statistics over relying solely on direct measurements.
  • Only data-driven models can be adjusted based on actual data, as opposed to generative models, which are based on underlying processes.
  • Models facilitate rigorous testing of theories, offering more robust validation compared to theoretical discussions.
  • They distill complex datasets into manageable parameters, aiding further analysis and interpretation.
  • While all models have limitations and are imperfect, certain models can provide substantial utility in application.

Fitting and Overfitting

  • One of the primary challenges in model fitting is the risk of overfitting, where a model becomes too complex and performs poorly on unseen data.

Rescorla-Wagner Model in Reinforcement Learning

  • The Rescorla-Wagner model successfully elucidates various elements of classical conditioning, particularly in understanding how learning occurs through associations.
  • An aspect of classical conditioning effectively represented by the Rescorla-Wagner model is the relationship between conditioned and unconditioned stimuli.
  • The model comprises mechanisms that can explain the phenomenon of extinction in classical conditioning, where the absence of reinforcement leads to the diminishing of a conditioned response.

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Explore the concepts of how models can enhance statistical analysis compared to direct measurements. Learn about the advantages and applications of using models in statistics.

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