---
res:
  bibo_abstract:
  - Simple board games, like Tic-Tac-Toe and CONNECT-4, play an important role not
    only in the development of mathematical and logical skills, but also in the emotional
    and social development. In this paper, we address the problem of generating targeted
    starting positions for such games. This can facilitate new approaches for bringing
    novice players to mastery, and also leads to discovery of interesting game variants.
    We present an approach that generates starting states of varying hardness levels
    for player 1 in a two-player board game, given rules of the board game, the desired
    number of steps required for player 1 to win, and the expertise levels of the
    two players. Our approach leverages symbolic methods and iterative simulation
    to efficiently search the extremely large state space. We present experimental
    results that include discovery of states of varying hardness levels for several
    simple grid-based board games. The presence of such states for standard game variants
    like 4×4 Tic-Tac-Toe opens up new games to be played that have never been played
    as the default start state is heavily biased. @eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Umair
      foaf_name: Ahmed, Umair
      foaf_surname: Ahmed
  - foaf_Person:
      foaf_givenName: Krishnendu
      foaf_name: Chatterjee, Krishnendu
      foaf_surname: Chatterjee
      foaf_workInfoHomepage: http://www.librecat.org/personId=2E5DCA20-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0002-4561-241X
  - foaf_Person:
      foaf_givenName: Sumit
      foaf_name: Gulwani, Sumit
      foaf_surname: Gulwani
  bibo_volume: 2
  dct_date: 2015^xs_gYear
  dct_language: eng
  dct_publisher: AAAI Press@
  dct_title: Automatic generation of alternative starting positions for simple traditional
    board games@
...