Requirements for Recognition and Rapid Response to Unfamiliar Events Outside of Agent Design Scope
This addresses the challenge of building general agents that can handle unforeseen situations, though it appears incremental as it builds on existing concepts like meta-knowledge.
The paper tackles the problem of enabling agents to recognize and respond to unfamiliar events outside their design scope, proposing a novel approach that combines domain-general meta-knowledge and metareasoning for fast, adaptive responses in open-world environments.
Regardless of past learning, an agent in an open world will face unfamiliar events outside of prior experience, existing models, or policies. Further, the agent will sometimes lack relevant knowledge and/or sufficient time to assess the situation and evaluate response options. How can an agent respond reasonably to situations that are outside of its original design scope? How can it recognize such situations sufficiently quickly and reliably to determine reasonable, adaptive courses of action? We identify key characteristics needed for solutions, review the state-of-the-art, and outline a proposed, novel approach that combines domain-general meta-knowledge (inspired by human cognition) and metareasoning. This approach offers potential for fast, adaptive responses to unfamiliar situations, more fully meeting the performance characteristics required for open-world, general agents.