Discounting in Strategy Logic

Abstract

Discounting is an important dimension in multi-agent systems as long as we want to reason about strategies and time. It is a key aspect in economics as it captures the intuition that the far-away future is not as important as the near future. Traditional verification techniques allow to check whether there is a winning strategy for a group of agents but they do not take into account the fact that satisfying a goal sooner is different from satisfying it after a long wait. In this paper, we augment Strategy Logic with future discounting over a set of discounted functions D, denoted SL[D]. We consider “until” operators with discounting functions: the satisfaction value of a specification in SL[D] is a value in [0, 1], where the longer it takes to fulfill requirements, the smaller the satisfaction value is. We motivate our approach with classical examples from Game Theory and study the complexity of model-checking SL[D]-formulas.

Cite

Text

Mittelmann et al. "Discounting in Strategy Logic." International Joint Conference on Artificial Intelligence, 2023. doi:10.24963/IJCAI.2023/26

Markdown

[Mittelmann et al. "Discounting in Strategy Logic." International Joint Conference on Artificial Intelligence, 2023.](https://mlanthology.org/ijcai/2023/mittelmann2023ijcai-discounting/) doi:10.24963/IJCAI.2023/26

BibTeX

@inproceedings{mittelmann2023ijcai-discounting,
  title     = {{Discounting in Strategy Logic}},
  author    = {Mittelmann, Munyque and Murano, Aniello and Perrussel, Laurent},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {225-233},
  doi       = {10.24963/IJCAI.2023/26},
  url       = {https://mlanthology.org/ijcai/2023/mittelmann2023ijcai-discounting/}
}