{
  "handle": "EmergentRuleSearch",
  "ref": "EmergentRuleSearch#9c19",
  "stub": "9c19",
  "semaId": "sema:EmergentRuleSearch#mh:SHA-256:9c193dcf9edc7b6c9eadab7da9f27ab778970100b5efc1dacfb5c334bfcf8792",
  "layer": "Physics",
  "category": "Dynamics",
  "gloss": "Vary the rules of simple agents in simulation to see which yield interesting collective behavior",
  "mechanism": "Start from a vague intuition about a phenomenon, define simple individual agents with tunable rules, and run the simulation while varying parameters. Observe under which conditions the phenomenon (such as a dominance hierarchy) emerges. The result is discovered, not specified, and deep learning is a large instance of the same search over unit rules.",
  "invariants": [
    "Rules apply to individual agents, not to the outcome",
    "The outcome is observed after running, not assumed"
  ],
  "failureModes": [
    "Oversimplified world that produces artifacts of the model",
    "Funding pressure to name the outcome before the search"
  ],
  "ring": 2,
  "tier": 3,
  "aliases": {},
  "buildsOn": [],
  "usedBy": [],
  "sources": {
    "research": [],
    "works": [],
    "homePage": false
  },
  "url": "/knowledge-graph/EmergentRuleSearch/",
  "graphUrl": "/knowledge-graph#EmergentRuleSearch",
  "directory": "/knowledge-graph/patterns.json"
}