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Agentic AI Atlas · minimax-regret-reasoning
lib-process:scientific-discovery--minimax-regret-reasoninga5c.ai
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LibraryProcess JSON

lib-process:scientific-discovery--minimax-regret-reasoning

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minimax-regret-reasoning json

Inspect the normalized record payload exactly as the atlas UI reads it.

File · generated-library/processes.yamlCluster · generated-library
Record JSON
{
  "id": "lib-process:scientific-discovery--minimax-regret-reasoning",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "minimax-regret-reasoning",
    "description": "Minimax Regret Reasoning Process - Minimize worst-case regret rather than\nutility, choosing actions that avoid largest potential disappointment across scenarios.",
    "libraryPath": "library/specializations/domains/science/scientific-discovery/minimax-regret-reasoning.js",
    "specialization": "scientific-discovery",
    "references": [
      "- Savage (1951). The Theory of Statistical Decision\n- Loomes & Sugden (1982). Regret Theory\n- Hayashi (2008). Regret Aversion and Opportunity Dependence\n- Stoye (2011). Minimax Regret"
    ],
    "example": "const result = await orchestrate('specializations/domains/science/scientific-discovery/minimax-regret-reasoning', {\n  domain: 'Investment Strategy',\n  alternatives: [{ name: 'aggressive' }, { name: 'moderate' }, { name: 'conservative' }],\n  scenarios: [{ name: 'bull_market' }, { name: 'bear_market' }, { name: 'stable' }]\n});",
    "usesAgents": [
      "bayesian-inference-engine"
    ]
  },
  "outgoingEdges": [
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "skill-area:data-analysis",
      "kind": "lib_requires_skill_area",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "skill-area:statistical-analysis",
      "kind": "lib_requires_skill_area",
      "attributes": {
        "weight": 0.7
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "skill-area:deep-web-research",
      "kind": "lib_requires_skill_area",
      "attributes": {
        "weight": 0.5
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "domain:scientific-discovery",
      "kind": "lib_applies_to_domain",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "role:research-engineer",
      "kind": "lib_involves_role",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "role:computational-scientist",
      "kind": "lib_involves_role",
      "attributes": {
        "weight": 0.7
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "workflow:experiment-design",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "workflow:peer-review-cycle",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 0.7
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "specialization:scientific-research-methods",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:scientific-discovery--minimax-regret-reasoning",
      "to": "specialization:scientific-discovery",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 0.9
      }
    }
  ],
  "incomingEdges": []
}