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Bayes vs Reinforcement

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Gordon Ovens

on 24 February 2013

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Transcript of Bayes vs Reinforcement

Bayesian updating
Reinforcement Heuristic Bayesian Updating (BEU) Using prior learned information when making decisions according to the laws of probability Reinforcement Heuristic (RH) - Win stay/ lose shift
- Pick choices associated with successful past outcomes The Experiment - First draw right BEU and RH coincide
- First draw left BEU and RH oppose - Treatment 1 & 2 same method, paid for drawing black balls
- Each treatment 60 periods of 2 draws
Main Findings - After right draw BEU and RH consistent (very low error rates)
- After left draw about half of participants (47.5% treatment 1 and 48.3% treatment 2) use RH and the rest BEU
- Treatment 3 only 28.2% use RH so removing the affect of the first draw reduces error rates People are different with about 50% following Bayesian principles and about 50% using a simplifying heuristic Take home message - Treatments 3 first draw was purely informational to try to avoid any form of affect
- 80 periods of 2 draws Dan Levin Gary Charness
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