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Semantic Games for Algorithmic Players

Genot, Emmanuel LU and Jacot, Justine LU (2012) Decisions, Games & Logic '12
Abstract
We describe a class of semantic extensive entailment game (eeg) with algorithmic players, related to game-theoretic semantics (gts), and generalized to classical first-order semantic entailment. Players have preferences for parsimonious spending of computational resources, and compute partial strategies, under qualitative uncertainty about future histories. We prove the existence of local preferences for moves, and strategic fixpoints, that allow to map eeg game-tree to the building rules and closure rules of Smullyan's semantic tableaux (st). We also exhibit a strategy profile that solves the fixpoint selection problem, and can be mapped to systematic constructions of semantic trees, yielding a completeness

result by translation.... (More)
We describe a class of semantic extensive entailment game (eeg) with algorithmic players, related to game-theoretic semantics (gts), and generalized to classical first-order semantic entailment. Players have preferences for parsimonious spending of computational resources, and compute partial strategies, under qualitative uncertainty about future histories. We prove the existence of local preferences for moves, and strategic fixpoints, that allow to map eeg game-tree to the building rules and closure rules of Smullyan's semantic tableaux (st). We also exhibit a strategy profile that solves the fixpoint selection problem, and can be mapped to systematic constructions of semantic trees, yielding a completeness

result by translation. We conclude on possible generalizations of our games. (Less)
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conference name
Decisions, Games & Logic '12
language
English
LU publication?
yes
id
93b7d9fd-ee16-4bf1-a6a7-c9153a94496c (old id 3172562)
date added to LUP
2012-11-22 15:08:25
date last changed
2016-04-16 10:49:11
@misc{93b7d9fd-ee16-4bf1-a6a7-c9153a94496c,
  abstract     = {We describe a class of semantic extensive entailment game (eeg) with algorithmic players, related to game-theoretic semantics (gts), and generalized to classical first-order semantic entailment. Players have preferences for parsimonious spending of computational resources, and compute partial strategies, under qualitative uncertainty about future histories. We prove the existence of local preferences for moves, and strategic fixpoints, that allow to map eeg game-tree to the building rules and closure rules of Smullyan's semantic tableaux (st). We also exhibit a strategy profile that solves the fixpoint selection problem, and can be mapped to systematic constructions of semantic trees, yielding a completeness<br/><br>
result by translation. We conclude on possible generalizations of our games.},
  author       = {Genot, Emmanuel and Jacot, Justine},
  language     = {eng},
  title        = {Semantic Games for Algorithmic Players},
  year         = {2012},
}