OCAIMAApr 12, 2016

Resource Allocation with Population Dynamics

arXiv:1604.03458v18 citations
Originality Synthesis-oriented
AI Analysis

This addresses resource allocation for populations with dynamic behaviors, but it appears incremental as it builds on prior work with a more general model.

The paper tackles resource-allocation problems by introducing a general behavioral model using a Markov chain for heterogeneous agent populations, showing that agent distribution across resources converges under certain assumptions.

Many analyses of resource-allocation problems employ simplistic models of the population. Using the example of a resource-allocation problem of Marecek et al. [arXiv:1406.7639], we introduce rather a general behavioural model, where the evolution of a heterogeneous population of agents is governed by a Markov chain. Still, we are able to show that the distribution of agents across resources converges in distribution, for suitable means of information provision, under certain assumptions. The model and proof techniques may have wider applicability.

Foundations

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