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Pascal Bouvry

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AAAI Conference 2022 Conference Paper

A Variant of Concurrent Constraint Programming on GPU

  • Pierre Talbot
  • Frédéric G Pinel
  • Pascal Bouvry

The number of cores on graphical computing units (GPUs) is reaching thousands nowadays, whereas the clock speed of processors stagnates. Unfortunately, constraint programming solvers do not take advantage yet of GPU parallelism. One reason is that constraint solvers were primarily designed within the mental frame of sequential computation. To solve this issue, we take a step back and contribute to a simple, intrinsically parallel, lock-free and formally correct programming language based on concurrent constraint programming. We then re-examine parallel constraint solving on GPUs within this formalism, and develop TURBO, a simple constraint solver entirely programmed on GPUs. TURBO validates the correctness of our approach and compares positively to a parallel CPU-based solver.

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KER Journal 2015 Journal Article

Adopting trust and assurance as indicators for the reassignment of responsibilities in multi-agent systems

  • Benjamin Gâteau
  • Moussa Ouedraogo
  • Christophe Feltus
  • Guy Guemkam
  • Grégoire Danoy
  • Marcin Seredynski
  • Samee U. Khan
  • Djamel Khadraoui

Abstract Multi-agent systems have been widely used in the literature, including for the monitoring of distributed systems. However, one of the unresolved issues in this technology remains in the reassignment of the responsibilities of monitoring agents when some of them become unable to meet their obligations. This paper proposes a new approach for solving this problem based on (a) the gathering of evidence on whether the agent can or cannot fulfil the tasks it has been assigned and (b) the reassignment of the task to alternative agents using their trust level as a selection parameter. A weather station case study is proposed as an instantiation of the proposed model.

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