Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Emergence of Social Punishment and Cooperation through Prior Commitments
Authors: The Anh Han
AAAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | All the analysis and numerical results in this paper (see next section) are obtained using evolutionary game theory (EGT) methods for finite populations (Nowak et al. 2004; Imhof, Fudenberg, and Nowak 2005). |
| Researcher Affiliation | Academia | The Anh Han School of Computing and Digital Futures Institute Teesside University, UK |
| Pseudocode | No | The paper includes mathematical formulations and payoff matrices but no pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any links to open-source code for the described methodology or state that code will be made available. |
| Open Datasets | No | The paper uses evolutionary game theory simulations rather than traditional datasets. It refers to game frameworks like 'Prisoner’s Dilemma' and 'finite populations' but does not provide access information for a public dataset. |
| Dataset Splits | No | The paper uses simulations based on evolutionary game theory. It does not describe traditional dataset splits such as training, validation, or testing sets. |
| Hardware Specification | No | The paper does not explicitly describe any specific hardware used for running its experiments (e.g., CPU, GPU models, or cloud resources). |
| Software Dependencies | No | The paper mentions using 'evolutionary game theory (EGT) methods' and 'Markov Chain' but does not specify any software names with version numbers (e.g., programming languages, libraries, or solvers). |
| Experiment Setup | Yes | Parameters: T = 4, R = 3, P = 0, S = 1; ϵ1 = ϵ2 = 1, δ1 = δ2 = 3; β = 0.1; population size N = 100. ... The average result is very similar to what was observed in Figure 1. When commitment is not an option (Figure 2a), the cooperation frequency is very low (8% on average), with no sample having more than 50% of cooperation. When punishment is not available (Figure 2b), cooperation is more frequent (41% on average), but defection is also prevalent (59% on average). In 45% of the samples there is more than 50% of cooperation. Finally, when both options are present (Figure 2c), a significantly higher level of cooperation is achieved (65% on average), with 75% of the samples having more than 50% of cooperation. |