{
  "id": "1907.12125",
  "version": "v1",
  "published": "2019-07-28T18:48:42.000Z",
  "updated": "2019-07-28T18:48:42.000Z",
  "title": "Decentralized Stochastic Control in Partially Nested Information Structures",
  "authors": [
    "Aditya Dave",
    "Andreas A. Malikopoulos"
  ],
  "categories": [
    "math.OC"
  ],
  "abstract": "In this paper, we analyze a network of agents in a partially nested information structure with a common ancestor. We present the prescription approach applied to different permutations of agents and a structural result for optimal prescriptions of control strategies. We demonstrate the proposed approach through an example that aims at establishing time-invariant domains of the prescriptions without assuming a Linear Quadratic Gaussian problem.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2019-07-28T18:48:42.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "partially nested information structure",
      "decentralized stochastic control",
      "linear quadratic gaussian problem",
      "common ancestor",
      "structural result"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}