SEARL: Joint Optimization of Policy and Tool Graph Memory for Self-Evolving Agents
SEARL: Joint Optimization of Policy and Tool Graph Memory for Self-Evolving Agents explores A framework for self-evolving agents that optimizes policy and tool graph memory for more practical and efficient learning in resource-constrained environments.. Commercial viability score: 7/10 in Agents.
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