Execute a bisimulation game to verify equivalence between AI agents.
npx skills add https://github.com/plurigrid/asi --skill bisimulation-game
Please help me install this Agent Skill. Skill: bisimulation-game Source: https://github.com/plurigrid/asi/tree/main/ies/music-topos/.ruler/skills/bisimulation-game Command: npx skills add https://github.com/plurigrid/asi --skill bisimulation-game
The Bisimulation Game provides a formal framework for dispersing skills across AI agents while preserving GF(3) conservation and enabling observational bridge types for synchronization.
Initialize a bisimulation session and perform rounds to verify equivalence between agents.
High-intent search queries and answers about installing and using this skill.
Bisimulation games identify system equivalence by executing rounds between attacker, defender, and arbiter agents. Initialize a session, run verification rounds to compare agent behaviors, and confirm observational equivalence while maintaining GF(3) conservation across state transitions.
GF(3) conservation ensures that algebraic field values remain consistent during state transitions when skills are distributed across agents. The bisimulation framework tracks and enforces this invariant throughout agent interactions to guarantee resilient skill dispersal and version-aware synchronization.
Yes. The bisimulation game integrates MCP Tasks protocol to enable agents to self-rewrite rules and enforce GF(3) conservation. This supports resilient skill dispersal and allows agents to adapt while maintaining observational-bridge synchronization across multi-agent environments.
Observational bridges synchronize agent states by establishing equivalence types that bridge different versions. In bisimulation games, these bridges allow agents with different implementations to maintain consistency while preserving GF(3) invariants and skill distribution across protocol versions.
Use bisimulation games when you need to verify that distributed agents maintain behavioral equivalence, preserve conservation laws during state changes, or require resilient skill dispersal with version compatibility. It's essential for systems where observational consistency across agent rounds must be formally proven.
BellaBeEvaluate artifacts against criteria and output verdicts with evidence tables.
plurigridCheck bisimilarity of derivation streams via coalgebraic observation.
0xRayAICoordinate multi-agent workflows and delegate tasks within the Xray framework.
plurigridConstruct directed bridges and perform hops across ordered locales with GF(3) conservation.
