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).