<?xml version="1.0" encoding="UTF-8"?>
<reference anchor="I-D.zhao-rtgwg-agentic-systems" target="https://datatracker.ietf.org/doc/html/draft-zhao-rtgwg-agentic-systems-00">
   <front>
      <title>A Framework for Network- and Compute-Aware Cross-Domain Agentic Systems</title>
      <author initials="D." surname="Zhao" fullname="Dan Zhao">
         <organization>Pengcheng Laboratory</organization>
      </author>
      <author initials="Q." surname="Li" fullname="Qing Li">
         <organization>Pengcheng Laboratory</organization>
      </author>
      <author initials="Y." surname="Wang" fullname="Yu Wang">
         <organization>Pengcheng Laboratory</organization>
      </author>
      <author initials="C." surname="Jiang" fullname="Changlin Jiang">
         <organization>Pengcheng Laboratory</organization>
      </author>
      <date month="October" day="21" year="2026" />
      <abstract>
	 <t>   Agentic systems can carry out tasks using agents, model services,
   data services, tools, and computing environments distributed across
   sites and administrative domains.  Dependencies among these
   components create communication and computing requirements that may
   evolve during execution.  Whether a proposed collaboration can
   satisfy those requirements depends on network connectivity and
   performance, computing capacity and readiness, data and model
   locality, and the policies governing resource use and data movement.

   This document describes a framework for cross-domain agentic
   collaboration that accounts for task dependencies and the network and
   computing conditions affecting communication and execution.  It
   outlines the roles and interactions of agents and their runtimes,
   infrastructure information functions, and resource-management
   functions.  The framework relates task dependencies to communication
   and computing requirements, with consideration of execution
   locations, data movement, and constraints spanning dependent
   activities.  It discusses the use of appropriately scoped domain
   information to assess alternative combinations of agents, services,
   and tools, together with the abstraction and updating of that
   information under partial visibility and independent domain policies.
   The framework also addresses adaptation to evolving dependencies and
   infrastructure conditions, including information overhead and the
   stability of decisions in large agent populations.

	 </t>
      </abstract>
   </front>
   <seriesInfo name="Internet-Draft" value="draft-zhao-rtgwg-agentic-systems-00" />
   
</reference>
