IJCAI 2023poster0 citations

Half-Positional Objectives Recognized by Deterministic Büchi Automata (Extended Abstract)

Patricia Bouyer, Antonio Casares, Mickael Randour, Pierre Vandenhove

Abstract

In two-player zero-sum games on graphs, the protagonist tries to achieve an objective while the antagonist aims to prevent it. Objectives for which both players do not need to use memory to play optimally are well-understood and characterized both in finite and infinite graphs. Less is known about the larger class of half-positional objectives, i.e., those for which the protagonist does not need memory (but for which the antagonist might). In particular, no characterization of half-positionality is known for the central class of ω-regular objectives. Here, we characterize objectives recognizable by deterministic Büchi automata (a class of ω-regular objectives) that are half-positional, both over finite and infinite graphs. This characterization yields a polynomial-time algorithm to decide half-positionality of an objective recognized by a given deterministic Büchi automaton.

Sister Conferences Best Papers: Agent-based and Multi-agent SystemsSister Conferences Best Papers: Constraint Satisfaction and Optimization
BibTeX
@inproceedings{ijcai2023p713,
  title     = {Half-Positional Objectives Recognized by Deterministic Büchi Automata (Extended Abstract)},
  author    = {Bouyer, Patricia and Casares, Antonio and Randour, Mickael and Vandenhove, Pierre},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Edith Elkind},
  pages     = {6420--6425},
  year      = {2023},
  month     = {8},
  note      = {Sister Conferences Best Papers},
  doi       = {10.24963/ijcai.2023/713},
  url       = {https://doi.org/10.24963/ijcai.2023/713},
}
Half-Positional Objectives Recognized by Deterministic Büchi Automata (Extended Abstract) · IJCAI 2023