Self-Evolving Agent: Equipped with Reflection and Memory Enhancement
SAGE boosts LLM performance with memory, reflection, and feedback enhancements for complex tasks. Improve decision-making and reduce errors with SAGE.
Large models still face challenges in areas like continuous decision-making in dynamic environments, lack of long-term memory, and limited context windows:
Meta-learning and multi-task learning methods aim to improve the transferability and adaptability of LLMs.
To address limited memory storage, strategies like MemGPT and MemoryBank manage memory differently.
However, these methods are usually task-specific and lack a unified framework.
An innovative framework has been proposed—Self-Evolving Agents with Reflection and Memory Enhancement (SAGE).
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