Zero-Sum Games between Mean-Field Teams: Reachability-Based Analysis under Mean-Field Sharing
Authors: Yue Guan, Mohammad Afshari, Panagiotis Tsiotras
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The ϵ-optimality of the resulting strategies is established in the original finite-population game, and the theoretical guarantees are verified by numerical examples. |
| Researcher Affiliation | Academia | Yue Guan, Mohammad Afshari, Panagiotis Tsiotras Georgia Institute of Technology {yguan44, mafshari, tsiotras}@gatech.edu |
| Pseudocode | No | The paper describes a dynamic programming recursion scheme with mathematical equations (8, 9, 10, 11) but does not provide a formal pseudocode block or algorithm. |
| Open Source Code | No | The paper does not provide any link or explicit statement about the availability of its source code. |
| Open Datasets | No | The paper uses numerical examples based on a specific problem setup ('a simple team game on a two-node graph', 'a ZS-MFTG with T =2') rather than a publicly available dataset with concrete access information. |
| Dataset Splits | No | The paper does not specify any training/test/validation dataset splits. It relies on numerical examples with a described problem setup. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU, GPU models, memory) used for running its numerical examples. |
| Software Dependencies | No | The paper does not mention any specific software or library names with version numbers that would be needed to replicate the experiments. |
| Experiment Setup | Yes | For both examples, the state spaces are X = {x1, x2} and Y = {y1, y2}, and the action spaces are U = {u1, u2} and V = {v1, v2}. The coordinator game values in Figure 3 are computed through discretization, where the two-dimensional simplexes P(X) and P(Y) are meshed into 1,000 bins. |