AgentCL: Toward Rigorous Evaluation of Continual Learning in Language Agents
An evaluation framework AgentCL for continual learning in agents is presented, centered on distinguishable task streams and metrics for CL properties, and MemProbe is developed, a probing method that stores interactions, insights, and skills while filtering unreliable experiences during consolidation.