Refining the imprecise meaning of non-determinism in the web by strategic games

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Abstract

Nowadays interactions with the World Wide Web are ubiquitous. Users interact through a number of steps consisting of site calls and handling results that can be automatized as orchestrations. Orchestration results have an inherent degree of uncertainty due to incomplete Web knowledge and orchestration semantics are characterized in terms of imprecise probabilistic choices. We consider two aspects in this imprecise semantic characterization. First, when local knowledge (even imprecise) of some part of the Web increases, this knowledge goes smoothly through the whole orchestration. We deal formally with this aspect introducing orchestration refinements. Second, we analyze refinement under uncertainty in the case of parallel composition. Uncertain knowledge is modeled by an uncertainty profile. Such profiles allow us to look at the uncertainty through a zero-sum game, called angel/daemon-game, or a/∂-game. We propose to use the structure of the Nash equilibria to refine uncertainty. In this case the information improves not through cooperation but through the a and ∂ competition.

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APA

Castro, J., Gabarro, J., & Serna, M. (2019). Refining the imprecise meaning of non-determinism in the web by strategic games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11683 LNAI, pp. 566–578). Springer Verlag. https://doi.org/10.1007/978-3-030-28377-3_47

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