{
  "title": "DiscoveryEngine",
  "domain": "Computational",
  "type": "Paper",
  "creators": [
    {
      "name": "Daniel A. Friedman"
    }
  ],
  "description": "The Discovery Engine presents a computational framework for automated scientific discovery using Active Inference principles. The system models the scientific discovery process as an inference problem...",
  "abstract": "The Discovery Engine presents a computational framework for automated scientific discovery using Active Inference principles. The system models the scientific discovery process as an inference problem, where hypotheses are generated, tested, and refined through free energy minimization, enabling structured exploration of research questions.",
  "keywords": [
    "Discovery Engine",
    "automated discovery",
    "Active Inference",
    "scientific reasoning",
    "hypothesis generation",
    "computational science"
  ],
  "methods": [
    {
      "name": "Active Inference",
      "description": "Applied active inference approach"
    },
    {
      "name": "Software pipeline design",
      "description": "Applied software pipeline design approach"
    }
  ],
  "key_findings": [
    "The Discovery Engine presents a computational framework for automated scientific discovery using Active Inference principles..",
    "The system models the scientific discovery process as an inference problem...."
  ],
  "related_papers": [
    "2023_NSFReporting",
    "2023_NaturalAIBased",
    "2025_AuBI"
  ],
  "checked_at": "2026-07-01T20:50:01Z"
}