Simulating Language 2015, pre-reading 7 questions

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* 1. Smith (2002) introduces the Iterated Learning Model. What is iterated learning?

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* 2. In that paper, I laid out a hierarchy of weight-update rules. Which of the following is an accurate summary of that hierarchy?

Not all weight-update rules allow an agent to learn an optimal signalling system. Of those that do, not all allow a population of agents to maintain an optimal signalling system over iterated learning. However, no weight update rule allows a population of agents to construct an optimal signalling system over iterated learning - optimal systems must come from some other mechanism.

Not all weight-update rules allow an agent to learn an optimal signalling system. Of those that do, not all allow a population of agents to construct an optimal signalling system over iterated learning. Of those that do, not all allow a population of agents to maintain an optimal signalling system over iterated learning.

All weight-update rules allow an agent to learn an optimal signalling system.

Not all weight-update rules allow an agent to learn an optimal signalling system. But those that do also allow a population of agents to maintain and construct an optimal signalling system over iterated learning.

Not all weight-update rules allow an agent to learn an optimal signalling system. Of those that do, not all allow a population of agents to maintain an optimal signalling system over iterated learning. Of those that do, not all allow a population of agents to construct an optimal signalling system over iterated learning.

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* 3. In your own words, what property of a weight update rule determines whether it can maintain and/or construct an optimal signalling system?

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* 4. Is there anything you would like me to know before the lecture - any stuff you want me to go over again, anything you struggled with, any worries you have?