International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Survey Paper on Developing Operating System's Complete Agentic Rex using Persistent Memory

Author(s) Ms. Pranita Mahesh Bobade, Mr. Aditya Sandeep Sarade, Mr Laxmikant Shashikant Deshpande, Dr. Prajwal Sopan Gaikwad
Country India
Abstract The rapid advancement of artificial intelligence has sparked a new wave of research into
agentic operating systems which are frameworks that enable machines to autonomously reason,
act, and interact with users through natural language. This survey explores the evolution of
such intelligent automation systems, focusing on the integration of Large Language Models
(LLMs) with operating system control, voice interfaces, and human privacy safety
mechanisms. We review key developments in the field, including memory-managed LLM
architectures like MemGPT, kernel-level agentic systems such as AIOS, and hybrid reasoning
action models like ReAct, which collectively illustrate the shift toward more adaptive and
context-aware automation. Furthermore, this paper situates the OS’s Agent framework within
this broader research landscape which is analysing its architectural concepts as part of the
emerging trend in trustworthy and modular AI-driven automation. By synthesizing insights
from prior works and comparing multiple agentic paradigms, this survey aims to highlight
ongoing challenges in ensuring safety, transparency, and cross-platform interoperability within
AI-augmented operating environments. Ultimately, the paper underscores the growing
convergence of natural language understanding, autonomous reasoning, and secure system
control as the foundation for next-generation intelligent operating systems
Keywords Operating systems , Autonomous , Large Language Model, Agent , Agentic, Agentic Memory, ReAct , AI Augmented
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-15
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.60537
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