---
res:
  bibo_abstract:
  - "We provide a learning-based technique for guessing a winning strategy in a parity
    game originating from an LTL synthesis problem. A cheaply obtained guess can be
    useful in several applications. Not only can the guessed strategy be applied as
    best-effort in cases where the game’s huge size prohibits rigorous approaches,
    but it can also increase the scalability of rigorous LTL synthesis in several
    ways. Firstly, checking whether a guessed strategy is winning is easier than constructing
    one. Secondly, even if the guess is wrong in some places, it can be fixed by strategy
    iteration faster than constructing one from scratch. Thirdly, the guess can be
    used in on-the-fly approaches to prioritize exploration in the most fruitful directions.\r\nIn
    contrast to previous works, we (i) reflect the highly structured logical information
    in game’s states, the so-called semantic labelling, coming from the recent LTL-to-automata
    translations, and (ii) learn to reflect it properly by learning from previously
    solved games, bringing the solving process closer to human-like reasoning.@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Jan
      foaf_name: Kretinsky, Jan
      foaf_surname: Kretinsky
      foaf_workInfoHomepage: http://www.librecat.org/personId=44CEF464-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0002-8122-2881
  - foaf_Person:
      foaf_givenName: Tobias
      foaf_name: Meggendorfer, Tobias
      foaf_surname: Meggendorfer
      foaf_workInfoHomepage: http://www.librecat.org/personId=b21b0c15-30a2-11eb-80dc-f13ca25802e1
    orcid: 0000-0002-1712-2165
  - foaf_Person:
      foaf_givenName: Maximilian
      foaf_name: Prokop, Maximilian
      foaf_surname: Prokop
  - foaf_Person:
      foaf_givenName: Sabine
      foaf_name: Rieder, Sabine
      foaf_surname: Rieder
  bibo_doi: 10.1007/978-3-031-37706-8_20
  bibo_volume: 13964
  dct_date: 2023^xs_gYear
  dct_identifier:
  - UT:001310786500020
  dct_isPartOf:
  - http://id.crossref.org/issn/0302-9743
  - http://id.crossref.org/issn/1611-3349
  - http://id.crossref.org/issn/9783031377051
  dct_language: eng
  dct_publisher: Springer Nature@
  dct_title: Guessing winning policies in LTL synthesis by semantic learning@
...