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The Aether Temporal Collective provides a sophisticated framework for maintaining coherent collective memory across large-scale AI agent networks. By utilizing Merkle-DAG branching timelines and holographic erasure coding, it effectively solves the 'forking history' problem where agents experience contradictory events or network partitions. This skill enables a resilient, fault-tolerant temporal topology where multiple narratives can coexist, merge, and solidify into a canonical consensus through narrative gravity and stake-weighted referendums, ensuring that distributed AI swarms maintain a shared sense of truth and history.