What is a bisimulation game in the context of AI?

It is a formal framework used to prove that two different systems (or AI agents) are observationally equivalent, meaning they react to the same inputs with the same transitions and cannot be distinguished by an observer.

Can this skill detect differences between AI models?

Yes, by acting as an 'Attacker,' the skill systematically tests transitions to find any points where one model's behavior diverges from another, providing a detailed migration or conflict report.

How does this skill help with multi-agent workflows?

It synchronizes skills and states across different environments like Claude, Cursor, and Codex, ensuring that updates in one platform are consistently and correctly mirrored in others.

What is GF(3) conservation?

GF(3) conservation is a ternary logic-based verification method used by the 'Arbiter' in the game to ensure that state transitions between systems are mathematically balanced and valid.

Bisimulation Game Sync

Name: Bisimulation Game Sync
Author: plurigrid

byplurigrid

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安全与测试

Verifies and synchronizes behavioral equivalence across AI agents using formal game-theoretic frameworks.

关于

The Bisimulation Game skill provides a rigorous framework for ensuring that multiple AI agents—such as Claude, Codex, and Cursor—maintain identical behavior and state consistency. By implementing a game-theoretic approach where an 'Attacker' identifies potential differences and a 'Defender' proves equivalence, this skill enables resilient skill dispersal and version-aware synchronization. It is ideal for developers managing complex multi-agent systems who need to guarantee that transition states are conserved and that decentralized agents remain observationally indistinguishable.

主要功能

GF(3) conservation logic for rigorous state transition tracking
Cross-platform synchronization for Claude, Codex, and Cursor
Automated equivalence reporting for temporal and derivational learning
2 GitHub stars
Game-theoretic verification using Attacker/Defender/Arbiter roles
Observational bridge types for version-aware skill migration

使用场景

Maintaining state consistency across different AI coding environments
Verifying that self-rewriting skills maintain behavioral parity after updates
Auditing multi-agent workflows to ensure no divergent behaviors emerge

关于

主要功能

GF(3) conservation logic for rigorous state transition tracking
Cross-platform synchronization for Claude, Codex, and Cursor
Automated equivalence reporting for temporal and derivational learning
2 GitHub stars
Game-theoretic verification using Attacker/Defender/Arbiter roles
Observational bridge types for version-aware skill migration

使用场景

Maintaining state consistency across different AI coding environments
Verifying that self-rewriting skills maintain behavioral parity after updates
Auditing multi-agent workflows to ensure no divergent behaviors emerge