Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.


A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.


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.

Constraint Games revisited

Authors: Anthony Palmieri, Arnaud Lallouet

IJCAI 2017 | Venue PDF | LLM Run Details | Input Tokens: 16,956 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 4,152 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.

Reproducibility Variable Result LLM Response
Research Type Experimental We have performed experiments on classical games of the Gamut suite [Nudelman et al., 2004]: Minimum Effort Game (MEG), Travelers Dilemma (TD), Dispersion Game (DG), Collaboration Game (CG), Arm Races (AR), El Farol Bar Game (EFBG) [Arthur, 1994] and Colonel Blotto (CB) Game [Roberson, 2006]. The results are presented in Table 1.
Researcher Affiliation Collaboration Anthony Palmieri, Arnaud Lallouet Huawei Technologies Ltd, French Research Center Greyc, University of Caen Normandie
Pseudocode Yes Algorithm 2.1 Enum
Open Source Code No The paper does not explicitly state that source code for the described methodology is publicly available or provide a link.
Open Datasets Yes We have performed experiments on classical games of the Gamut suite [Nudelman et al., 2004]
Dataset Splits No The paper does not provide specific details on training, validation, or test dataset splits.
Hardware Specification Yes Experiments have been run on a Intel Xeon E5-1660 with 32 GB of RAM, Java 8 and Windows 7.
Software Dependencies Yes We have implemented a new solver for Constraint Games on top of the constraint solver Choco v4 [Prud homme et al., 2017].
Experiment Setup Yes For all experiments, we have applied a lexicographic heuristics on the choice of variables and a min value heuristics on the choice of the values.