Bayesian Statistics and Bayesian Cognitive Modeling (BayesCog), Part 2
UKE, Hamburg (hybrid), 2023
Dr. Lei Zhang, University of Birmingham, UK
Materials from Part 1 can be found here.
Teaching materials for my BayesCog workshop, Part 2.
Dec. 2023:
- Updated some recent literature and materials
- Added conceptualizations of cognitive & computational modeling
- Included a new section on the "Principled workflow"
May 2021:
- Added Crawley & Zhang 2020 for explaining optimal learning rates
- Updated some recent literature
- Added Cognitive Modeling Academy Hamburg when introducing further courses
Feb. 2020:
- Add details of the interpretation on RL parameters
| Folder | Task | 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 |
For bug reports, please contact Lei Zhang (l.zhang.13@bham.ac.uk, or @lei_zhang_lz).
Thanks to Markdown Cheatsheet and shields.io.
This license (CC BY-NC 4.0) gives you the right to re-use and adapt, as long as you note any changes you made, and provide a link to the original source. Read here for more details.
