A Bayesian Theory of Conformity in Collective Decision Making
Authors: Koosha Khalvati, Saghar Mirbagheri, Seongmin A. Park, Jean-Claude Dreher, Rajesh PN Rao
NeurIPS 2019 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The viability of our framework is demonstrated on two different experiments, a consensus task with 120 subjects and a volunteer s dilemma task with 29 subjects, each with multiple conditions. We tested our framework on two different collective decision making experiments involving human subjects: a consensus task and a volunteer s dilemma task. Our normative Bayesian framework explained and predicted human behavior well on both of these tasks. |
| Researcher Affiliation | Academia | Koosha Khalvati Paul G. Allen School of CSE University of Washington EMAIL Saghar Mirbagheri Department of Psychology New York University EMAIL Seongmin A. Park Center for Mind and Brain University of California, Davis EMAIL Jean-Claude Dreher Neuroeconomics Lab Institut des Sciences Cognitives Marc Jeannerod EMAIL Rajesh P. N. Rao Paul G. Allen School of CSE & Center for Neurotechnology University of Washington EMAIL |
| Pseudocode | No | The paper describes models and equations but does not contain any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any links to open-source code or explicitly state that code is made available. |
| Open Datasets | Yes | We analyzed the behavioral data of [23] with 120 subjects performing consensus decision making in groups of N = 6 or N = 4 members. We analyzed the behavioral data from a Volunteer s Dilemma task [24] where 29 subjects played 12 games of a multi-round thresholded Public Goods Game (PGG). |
| Dataset Splits | Yes | In addition to fitting accuracy, we calculated Leave-One-Out Cross Validation (LOOCV) accuracy where at each iteration, the left-out data point was one whole game. |
| Hardware Specification | No | The paper does not specify the hardware used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific version numbers for software dependencies. |
| Experiment Setup | Yes | For the conformity (level-0) model, there was only one free parameter, the decay rate λ. For the POMDP model (level-1)... Overall, the level-1 model had two free parameters (decay rate and winning value) for each subject. For the level-2 To M model... Therefore, the free parameters of the level-2 (and higher) models are the same as the level-1 model. For the models for all levels of To M, there are 3 free parameters in total, i.e., λ, α0 and β0. The RL model had 5 parameters in total. The first parameter was a reward for generating public good... The next two parameters determined the chance of producing public good for k = 2 versus k = 4, and were used to define the initial Q-value of each action. The final two free parameters determined the learning rate... |