{
  "id": "2109.09055",
  "version": "v1",
  "published": "2021-09-19T03:43:10.000Z",
  "updated": "2021-09-19T03:43:10.000Z",
  "title": "Analysis, Optimization, Control, and Learning of Cyber-Physical Systems",
  "authors": [
    "Andreas Malikopoulos"
  ],
  "comment": "12",
  "categories": [
    "math.OC"
  ],
  "abstract": "The overarching goal of the Information and Decision Science (IDS) Lab is to enhance understanding of complex systems and establish a holistic, multifaceted approach using scalable data and informatics to developing rigorous mathematical models and decentralized control algorithms for making engineering complex systems able to realize how to improve their performance over time while interacting with their environment. The emphasis is on applications related to connected and automated vehicles (CAVs), sociotechnical systems, energy and sustainable systems, smart cities and connected communities.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2021-09-19T03:43:10.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "cyber-physical systems",
      "optimization",
      "decision science",
      "smart cities",
      "decentralized control algorithms"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}