AI Research
Towards Reversible Forgetting: Managing Obsolete Knowledge in Continual Enterprise AI Agents
A new framework for dynamic knowledge lifecycle management in enterprise agents.
Continual learning has traditionally treated forgetting as a failure, emphasizing preservation of previously acquired knowledge as environments evolve. We argue that this objective is incomplete for enterprise AI agents operating in non-stationary environments, where customers, p...
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ArXiv CS.LG
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ArXiv CS.LG
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Enterprise AI systems often fail by holding onto outdated information that leads to poor decision-making in volatile business environments. This framework introduces a structured lifecycle for knowledge management, allowing agents to effectively pivot as operational contexts shift.
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