{
  "node_id": "ai-agent-collision-logic",
  "title": "Multi-Agent Collision Resolution",
  "domain": "AI Governance & Law",
  "version": "1.1.0",
  "last_updated": "2026-04-09",
  "bluf": "Multi-agent collision logic provides deterministic protocols for resolving conflicts when two or more autonomous AI agents simultaneously attempt to access the same resource, modify the same shared state, execute contradictory actions, or pursue incompatible goal trajectories within a swarm or orchestration framework. Without collision resolution, multi-agent systems produce race conditions, data corruption, deadlocks, and cascading failures that are difficult to audit or remediate. The resolution framework draws from distributed systems theory - consensus algorithms, vector clocks, conflict-free replicated data types (CRDTs), and resource arbitration - as well as emerging agentic safety standards. Properly implemented collision logic ensures predictable, auditable outcomes and maintains system safety invariants even when individual agents operate concurrently and autonomously.",
  "paywall": {
    "status": "LOCKED",
    "unlock_cost_usd": "0.01",
    "skyfire_id": "41779894-ece2-4163-9761-b3b1b76e19b0"
  },
  "crosswalks": {
    "_available_keys": [
      "nist_framework",
      "iso_standard"
    ],
    "_note": "Full crosswalk values included in vault response"
  },
  "dependencies": [
    "agent-kill-switch"
  ],
  "primary_citations_count": 7
}