AINeutralarXiv – CS AI · 14h ago6/10
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SEARL: Joint Optimization of Policy and Tool Graph Memory for Self-Evolving Agents
Researchers introduce SEARL, a self-evolving agent framework that optimizes policy and tool memory jointly to enable efficient learning in resource-constrained environments. The approach addresses limitations of existing methods by constructing structured experience memory that densifies sparse rewards and facilitates tool reuse across tasks.