English

Resource allocation under uncertainty: an algebraic and qualitative treatment

Artificial Intelligence 2018-05-18 v1 Computer Science and Game Theory

Abstract

We use an algebraic viewpoint, namely a matrix framework to deal with the problem of resource allocation under uncertainty in the context of a qualitative approach. Our basic qualitative data are a plausibility relation over the resources, a hierarchical relation over the agents and of course the preference that the agents have over the resources. With this data we propose a qualitative binary relation \unrhd between allocations such that FG\mathcal{F}\unrhd \mathcal{G} has the following intended meaning: the allocation F\mathcal{F} produces more or equal social welfare than the allocation G\mathcal{G}. We prove that there is a family of allocations which are maximal with respect to \unrhd. We prove also that there is a notion of simple deal such that optimal allocations can be reached by sequences of simple deals. Finally, we introduce some mechanism for discriminating {optimal} allocations.

Keywords

Cite

@article{arxiv.1805.06864,
  title  = {Resource allocation under uncertainty: an algebraic and qualitative treatment},
  author = {Franklin Camacho and Gerardo Chacón and Ramón Pino Peréz},
  journal= {arXiv preprint arXiv:1805.06864},
  year   = {2018}
}
R2 v1 2026-06-23T01:58:59.949Z