• Computer Science > Artificial Intelligence [Submitted on 3 Feb 2026] Title:MAPLE: A Sub-Agent Architecture for Memory, Learning, and Personalization in Agentic AI Systems View PDF HTML (experimental)Abstract:Large language model (LLM) agents have emerged as powerful tools for complex tasks, yet their ability to adapt to individual users remains fundamentally limited. • We argue this limitation stems from a critical architectural conflation: current systems treat memory, learning, and personalization as a unified capability rather than three distinct mechanisms requiring different infrastructure, operating on different timescales, and benefiting from independent optimization. • We propose MAPLE (Memory-Adaptive Personalized LEarning), a principled decomposition where Memory handles storage and retrieval infrastructure; Learning extracts intelligence from accumulated interactions asynchronously; and Personalization applies learned knowledge in real-time within finite context budgets. • Each component operates as a dedicated sub-agent with specialized tooling and well-defined interfaces. • Experimental evaluation on the MAPLE-Personas benchmark demonstrates that our decomposition achieves a 14.6% improvement in personalization score compared to a stateless baseline (p < 0.01, Cohen’s d = 0.95) and increases trait incorporation rate from 45% to 75% – enabling agents that genuinely learn and adapt. • Submission history From: Deepak Babu Piskala [view email][v1] Tue, 3 Feb 2026 03:46:39 UTC

Article Summaries:

  • Computer Science > Artificial Intelligence [Submitted on 3 Feb 2026] Title:MAPLE: A Sub-Agent Architecture for Memory, Learning, and Personalization in Agentic AI Systems View PDF HTML (experimental)Abstract:Large language model (LLM) agents have emerged as powerful tools for complex tasks, yet their ability to adapt to individual users remains fundamentally limited. We argue this limitation stems from a critical architectural conflation: current systems treat memory, learning, and personalization as a unified capability rather than three distinct mechanisms requiring different infrastructure,

Sources: