{
  "annotation_id": "78147f7c-42d6-4768-82df-d98302447ec5",
  "date_created": "2026-02-17T05:53:16.247000Z",
  "date_modified": "2026-02-17T05:53:16.247000Z",
  "file_hash": "5de9170e0d865655b4e6467adf86b1f02db142fc9c2871c4295112453996a07a",
  "private": false,
  "record": {
    "abstract": "How should cities invest to improve social welfare when individuals respond strategically to local conditions? We model this question using a game-theoretic version of Schelling\u0027s bounded neighbourhood model, where agents choose neighbourhoods based on concave, non-monotonic utility functions reflecting local population. While naive improvements may worsen outcomes - analogous to Braess\u0027 paradox - we show that carefully designed, small-scale investments can reliably align individual incentives with societal goals. Specifically, modifying utilities at a total cost of at most $0.81 \\epsilon^2 \\cdot \\texttt{opt}$ guarantees that every resulting Nash equilibrium achieves a social welfare of at least $\\epsilon \\cdot \\texttt{opt}$, where $\\texttt{opt}$ is the optimum social welfare. Our results formalise how targeted interventions can transform supra-negative outcomes into supra-positive returns, offering new insights into strategic urban planning and decentralised collective behaviour.",
    "arxiv_id": "2601.08642",
    "authors": [
      "Martin Gairing",
      "Adrian Vetta",
      "Zhanzhan Zhao"
    ],
    "categories": [
      "cs.GT",
      "econ.TH"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "Cities at Play: Improving Equilibria in Urban Neighbourhood Games",
    "url": "https://arxiv.org/abs/2601.08642",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "c4e079ed-608b-4aea-9832-b041e36fdec3",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}