This repository contains all materials (slides & codes) from my BayesCog_v0.2 workshop.
UKE, Hamburg, 2018
- Unpack reinforcement learning model
- Add details of model comparison
- Add posterior predictive check for RL models
- Add justification for RPE signal (in model-based fMRI)
| Folder | Task | Model |
|---|---|---|
| 00.cheatsheet | NA | NA |
| 01.R_basics | NA | NA |
| 02.binomial_globe | Globe toss | Binomial Model |
| 03.bernoulli_coin | Coin flip | Bernoulli Model |
| 04.regression_height | Observed weight and height | Linear regression model |
| 05.regression_height_poly | Observed weight and height | Linear regression model |
| 06.reinforcement_learning | 2-armed bandit task | Simple reinforcement learning (RL) |
| 07.optm_rl | 2-armed bandit task | Simple reinforcement learning (RL) |
| 08.compare_models | Probabilistic reversal learning task | Simple and fictitious RL models |
| 09.debugging | Memory Retention | Exponential decay model |
| 10.model_based | 2-armed bandit task | Simple RL model |
| 11.delay_discounting | Delay discounting task | Hyperbolic and exponential discounting model |
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