Computational Results for Extensive-Form Adversarial Team Games
Authors: Andrea Celli, Nicola Gatti
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we empirically evaluate the scalability of our algorithms in random games and the inefficiency caused by partial or null communication. |
| Researcher Affiliation | Academia | Andrea Celli, Nicola Gatti Politecnico di Milano Piazza Leonardo da Vinci, 32 Milano, Italy {andrea.celli, nicola.gatti}@polimi.it |
| Pseudocode | Yes | Algorithm 1 Hybrid Column Generation |
| Open Source Code | No | The paper does not provide any explicit statement about releasing source code, nor does it include a link to a code repository for the methodology described. |
| Open Datasets | No | Our experimental setting is based on randomly generated STSA-EF-TGs. The random game generator takes as inputs: the number n of players, a probability distribution over the number of actions available at each information set, the maximum depth d of the tree, and a parameter ν for tuning the information structure of the tree. |
| Dataset Splits | No | The paper describes generating 'game instances' for evaluation but does not specify traditional train/validation/test dataset splits. The experimental setup is based on randomly generated game instances, not pre-existing datasets with defined splits. |
| Hardware Specification | Yes | All the algorithms are executed on a UNIX computer with 2.33GHz CPU and 128 GB RAM. |
| Software Dependencies | Yes | The algorithms are implemented in Python 2.7.6, adopting GUROBI 7.0 for LPs and ILPs, AMPL 20170207 and global optimization solver BARON 17.1.2 (Tawarmalani and Sahinidis 2005). |
| Experiment Setup | Yes | We generate 20 game instances for each combination of the following parameters values: n P t3, 4, 5u, d P tn, . . . , 15u with step size 1 (i.e., for games with 5 players, d P t5, 6, . . . , 15u), ν P t0.0, 0.25, 0.5, 0.75, 1.0u. For simplicity, we fix the branching factor to 2... We set a time limit to the algorithms of 60 minutes. |