Bayesian ascent Monte Carlo Options: :predict-candidates (false by default) - output all samples rather than just those with increasing log-weight
Bayesian ascent Monte Carlo Options: :predict-candidates (false by default) - output all samples rather than just those with increasing log-weight
(->entry bandit-id value past-reward)
Positional factory function for class anglican.bamc.entry.
Positional factory function for class anglican.bamc.entry.
(->multiarmed-bandit arms new-arm-belief new-arm-count new-arm-drawn)
Positional factory function for class anglican.bamc.multiarmed-bandit.
Positional factory function for class anglican.bamc.multiarmed-bandit.
(add-bandit-predict state)
add bandit arms and counts as a predict
add bandit arms and counts as a predict
(add-trace-predict state)
adds trace as a predict
adds trace as a predict
(backpropagate state)
back propagate reward to bandits
back propagate reward to bandits
(bandit-id smp state)
Bayesian belief
Bayesian belief
(bb-as-prior belief)
returns a belief for use as a prior belief
returns a belief for use as a prior belief
(bb-sample belief)
returns a random sample from the belief distribution
returns a random sample from the belief distribution
(bb-sample-mean belief)
returns a random sample from the mean belief distribution
returns a random sample from the mean belief distribution
(bb-update belief evidence)
updates belief based on the evidence
updates belief based on the evidence
uninformative mean reward belief
uninformative mean reward belief
(map->entry m__7585__auto__)
Factory function for class anglican.bamc.entry, taking a map of keywords to field values.
Factory function for class anglican.bamc.entry, taking a map of keywords to field values.
(map->multiarmed-bandit m__7585__auto__)
Factory function for class anglican.bamc.multiarmed-bandit, taking a map of keywords to field values.
Factory function for class anglican.bamc.multiarmed-bandit, taking a map of keywords to field values.
(not-a-value? value)
true when new value must be sampled
true when new value must be sampled
(record-choice state bandit-id value past-reward)
records random choice in the state
records random choice in the state
(reward-belief sum sum2 cnt)
returns reification of bayesian belief about the mean reward of an arm
returns reification of bayesian belief about the mean reward of an arm
(select-value bandit log-p)
selects value corresponding to the best arm
selects value corresponding to the best arm
(update-bandit bandit value reward)
updates bandit's belief
updates bandit's belief
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