Beyond Sliding Windows: Learning to Manage Memory in Non-Markovian Environments

This article, sourced from ArXiv, likely discusses advancements in memory management techniques for AI models, particularly those operating in complex, non-Markovian environments. The title suggests a move away from traditional methods like sliding windows, implying the exploration of more sophisticated approaches to handle long-range dependencies and context within the model's memory. The focus is on improving the ability of AI to retain and utilize information over extended periods, which is crucial for tasks requiring reasoning, planning, and understanding of complex sequences.