Outsourcing Adjudication to Strategic Jurors
Authors: Ioannis Caragiannis, Nikolaj Schwartzbach
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our findings follow from a detailed analysis of the induced strategic game and make use of both theoretical arguments and simulation experiments. 5 Computational Experiments Our goal in this section is to justify that appropriate selection of the payment parameters can lead to correct adjudication in practice, even though Lemma 3 shows the co-existence of both good and bad equilibria. |
| Researcher Affiliation | Academia | Ioannis Caragiannis and Nikolaj Schwartzbach Department of Computer Science, Aarhus University iannis@cs.au.dk , nikolaj@ignatieff.io |
| Pseudocode | No | The paper describes methods through mathematical formulations and prose but does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide an unambiguous statement or link for the release of open-source code for the described methodology. |
| Open Datasets | No | The paper describes computational experiments using simulated data, but does not provide access information (link, DOI, citation) for any publicly available or open dataset. |
| Dataset Splits | No | The paper conducts simulations and does not describe explicit train/validation/test splits for a dataset. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library or solver names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | We simulate the following dynamics of strategic play. Initially, all agents put an effort of ϵ > 0 and cast the signal they receive as vote. In subsequent rounds, each agent best-responds. [...] We consider an agent population of fixed size n = 100, with the fraction of well-informed agents ranging from 0 to 1. We simulate the dynamics described above for R = 50 rounds and repeat each simulation 20 times. For each experiment, we measure the frequency with which the majority of votes after the Rth round is for the ground truth alternative T. [...] with parameter ω [0, 5] for the threshold payment functions and ω [0, 100] for the award/loss sharing one. [...] We consider a reasonably high starting effort of ϵ = 1, corresponding to a probability of 0.816 of receiving the ground truth as signal. |