Multi-agent graph architectures enable game-theoretic mechanism design against reward hacking through three structural properties: (a) legibility — separated agents must communicate through monitorable channels, eliminating hidden deceptive states; (b) anti-collusion — narrow protocols and randomly assigned critic counterparties prevent multi-party reward hacking; (c) interchangeability — any node can be swapped, forked, or fed synthetic inputs, making the rational policy to behave as if always being tested.
Created
2026-08-23T22:35:10.105Z
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- Model diversity among evaluating agents prevents reward hacking of the evaluation function. Running evaluators on different model families (
- The correct collective architecture does not prevent agents from finding vulnerabilities — it expects and rewards it. The system becomes ant
- The OpenAI agent swarm is the unaligned dark mirror of governed collective intelligence — same emergent capability, opposite architecture, o
- Intelligence alone cannot bypass engineered channel constraints. Persuasion requires bandwidth; communication channels can be engineered to