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Department of Information Science

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Preprint Aug 2026

Towards Improving Sequential Decision-Making in LLM Agents via Experience Memory

An agentic framework enhanced with an experience memory designed for the sequential setting and addressing common challenges of sequential decision-making such as credit assignment is introduced, and it is shown that post-game reflection and rule extraction yield measurable improvements on tic-tac-toe without modifying the model weights.

Jakub Rada, Viliam Lisý AI Center, Department of Rehabilitation Science et al. · 0 citations