English

Diffusion Approximations for Controlled Weakly Interacting Large Finite State Systems with Simultaneous Jumps

Probability 2016-03-31 v1

Abstract

We consider a rate control problem for an NN-particle weakly interacting finite state Markov process. The process models the state evolution of a large collection of particles and allows for multiple particles to change state simultaneously. Such models have been proposed for large communication systems (e.g. ad hoc wireless networks) but are also suitable for other settings such as chemical-reaction networks. An associated diffusion control problem is presented and we show that the value function of the NN-particle controlled system converges to the value function of the limit diffusion control problem as NN\to\infty. The diffusion coefficient in the limit model is typically degenerate, however under suitable conditions there is an equivalent formulation in terms of a controlled diffusion with a uniformly non-degenerate diffusion coefficient. Using this equivalence, we show that near optimal continuous feedback controls exist for the diffusion control problem. We then construct near asymptotically optimal control policies for the NN-particle system based on such continuous feedback controls. Results from some numerical experiments are presented.

Keywords

Cite

@article{arxiv.1603.09001,
  title  = {Diffusion Approximations for Controlled Weakly Interacting Large Finite State Systems with Simultaneous Jumps},
  author = {Amarjit Budhiraja and Eric Friedlander},
  journal= {arXiv preprint arXiv:1603.09001},
  year   = {2016}
}

Comments

41 Pages

R2 v1 2026-06-22T13:21:04.420Z