Resource allocation under uncertainty: an algebraic and qualitative treatment
Camacho, Franklin, Chacón, Gerardo, Peréz, Ramón Pino
–arXiv.org Artificial Intelligence
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 $\mathcal{F}\unrhd \mathcal{G}$ has the following intended meaning: the allocation $\mathcal{F}$ produces more or equal social welfare than the allocation $\mathcal{G}$. 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.
arXiv.org Artificial Intelligence
May-17-2018
- Country:
- Europe
- Spain > Andalusia
- Seville Province > Seville (0.04)
- United Kingdom > England
- Cambridgeshire > Cambridge (0.14)
- Spain > Andalusia
- North America > United States
- District of Columbia > Washington (0.04)
- South America
- Ecuador (0.04)
- Venezuela > Mérida State
- Merida (0.04)
- Europe
- Genre:
- Research Report (0.64)
- Technology: