Natural Strategic Ability in Stochastic Multi-Agent Systems
Abstract
Strategies synthesized using formal methods can be complex and often require infinite memory, which does not correspond to the expected behavior when trying to model Multi-Agent Systems (MAS). To capture such behaviors, natural strategies are a recently proposed framework striking a balance between the ability of agents to strategize with memory and the complexity of the model-checking problem, but until now has been restricted to fully deterministic settings. For the first time, we consider the probabilistic temporal logics PATL and PATL∗ under natural strategies (NatPATL and NatPATL∗). As main result we show that, in stochastic MAS, NatPATL model-checking is NP-complete when the active coalition is restricted to deterministic strategies. We also give a 2NEXPTIME complexity result for NatPATL∗ with the same restriction. In the unrestricted case, we give an EXPSPACE complexity for NatPATL and 3EXPSPACE complexity for NatPATL*.
Cite
Text
Berthon et al. "Natural Strategic Ability in Stochastic Multi-Agent Systems." AAAI Conference on Artificial Intelligence, 2024. doi:10.1609/AAAI.V38I16.29678Markdown
[Berthon et al. "Natural Strategic Ability in Stochastic Multi-Agent Systems." AAAI Conference on Artificial Intelligence, 2024.](https://mlanthology.org/aaai/2024/berthon2024aaai-natural/) doi:10.1609/AAAI.V38I16.29678BibTeX
@inproceedings{berthon2024aaai-natural,
title = {{Natural Strategic Ability in Stochastic Multi-Agent Systems}},
author = {Berthon, Raphaël and Katoen, Joost-Pieter and Mittelmann, Munyque and Murano, Aniello},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2024},
pages = {17308-17316},
doi = {10.1609/AAAI.V38I16.29678},
url = {https://mlanthology.org/aaai/2024/berthon2024aaai-natural/}
}