Centralized versus Personalized Commitments and Their Influence on Cooperation in Group Interactions
Authors: The Anh Han, Luis Moniz Pereira, Luis A. Martinez-Vaquero, Tom Lenaerts
AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Using methods from Evolutionary Game Theory, this paper shows that, in the context of Public Goods Game, much higher levels of cooperation can be achieved through such centralized commitment management. It provides a more efficient mechanism for dealing with commitment free-riders... Our analysis is carried out in the context of the Public Goods Game (PGG)... Analytical and numerical results obtained here use EGT methods for finite populations. |
| Researcher Affiliation | Academia | 1 School of Computing and Digital Futures Institute, Teesside University, UK 2 NOVALINCS, Faculdade de Ciˆencias e Tecnologia, Universidade Nova de Lisboa, Portugal 3 Institute of Cognitive Sciences and Technologies, National Research Council of Italy (ISTC-CNR), Italy 4 MLG, D epartement d Informatique, Universit e Libre de Bruxelles, Belgium 5 AI lab, Computer Science Department, Vrije Universiteit Brussel, Belgium |
| Pseudocode | No | The paper describes models and equations but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statements or links regarding the availability of its source code. |
| Open Datasets | No | The paper models a Public Goods Game and uses Evolutionary Game Theory simulations, which are not based on a traditional publicly available dataset. There is no mention of a specific dataset or its access information. |
| Dataset Splits | No | The paper describes simulation parameters and population dynamics within Evolutionary Game Theory but does not refer to traditional dataset splits like training, validation, or test sets. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models) used to run the simulations. |
| Software Dependencies | No | The paper mentions using "EGT methods" but does not specify any ancillary software dependencies or their version numbers (e.g., programming languages, libraries, or simulation software versions). |
| Experiment Setup | Yes | Parameters: N = 5, Z = 100, r = 3, δ = 4, ϵ = 0.5, β = 0.25, F = 4; ρN = 1/Z denotes the neutral fixation probability. |