Episodic Memory in Agentic Frameworks: Suggesting Next Tasks

Sandro Rama Fiorini, Leonardo G. Azevedo, Raphael M. Thiago, Valesca M. de Sousa, Anton B. Labate +1 more
11/21/2025
cs.MAcs.AIcs.LG

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Abstract

Agentic frameworks powered by Large Language Models (LLMs) can be useful tools in scientific workflows by enabling human-AI co-creation. A key challenge is recommending the next steps during workflow creation without relying solely on LLMs, which risk hallucination and require fine-tuning with scarce proprietary data. We propose an episodic memory architecture that stores and retrieves past workflows to guide agents in suggesting plausible next tasks. By matching current workflows with historical sequences, agents can recommend steps based on prior patterns.

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Cite this paper

@article{fiorini2025episodic,
  title  = {Episodic Memory in Agentic Frameworks: Suggesting Next Tasks},
  author = {Sandro Rama Fiorini and Leonardo G. Azevedo and Raphael M. Thiago and Valesca M. de Sousa and Anton B. Labate and Viviane Torres da Silva},
  year   = {2025},
  eprint = {2511.17775},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2511.17775v1}
}

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