



Network Working Group                                              Z. Du
Internet-Draft                                              China Mobile
Intended status: Informational                              30 June 2025
Expires: 1 January 2026


  Use Cases and Requirements of AI Agent Communication from 6G Aspect
              draft-du-ai-agent-communication-6g-aspect-00

Abstract

   AI Agent can do some tasks as an assistant to human beings.  During
   the task process, the Agent may need to connect to other Agents with
   different skills relative to the task.  The Agent to Agent
   communication is a new kind of traffic for Internet, and some new
   requirements for networking are proposed.  This document talks about
   the requirements and key issues of global AI agent communication
   towards 6G.  Some 6G related use cases from 3GPP documents are
   introduced.  After that, the related requirements for the AI Agent
   Communication Network (ACN) are proposed, and potential ACN
   frameworks and standardization works for the AI Agent Communication
   are also discussed.

Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
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   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on 1 January 2026.






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Copyright Notice

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   document authors.  All rights reserved.

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   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Use Case on AI-agents Communication . . . . . . . . . . . . .   3
     2.1.  Grouping During Task Process  . . . . . . . . . . . . . .   3
     2.2.  Potential Requirements for ACN  . . . . . . . . . . . . .   5
   3.  Use Case on 6G System Assisted AI Agent Service . . . . . . .   5
     3.1.  Assistance of Network . . . . . . . . . . . . . . . . . .   5
     3.2.  Potential Requirements for ACN  . . . . . . . . . . . . .   6
   4.  Use Case on Collaborative AI Agents . . . . . . . . . . . . .   6
     4.1.  Collaboration of AI Agent . . . . . . . . . . . . . . . .   6
     4.2.  Potential Requirements for ACN  . . . . . . . . . . . . .   7
   5.  Cooperation Layer in Agent Communication  . . . . . . . . . .   7
   6.  Communication Modes of ACN  . . . . . . . . . . . . . . . . .   8
   7.  Framework of Centralized Agent Communication Platform . . . .  10
   8.  Framework of Decentralized Agent Cooperation  . . . . . . . .  12
   9.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  13
   10. Security Considerations . . . . . . . . . . . . . . . . . . .  13
   11. Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  13
   12. References  . . . . . . . . . . . . . . . . . . . . . . . . .  13
     12.1.  Normative References . . . . . . . . . . . . . . . . . .  14
     12.2.  Informative References . . . . . . . . . . . . . . . . .  14
   Appendix A.  Service Flows of AI-agents Communication . . . . . .  14
     A.1.  Pre-conditions  . . . . . . . . . . . . . . . . . . . . .  14
     A.2.  Service Flows . . . . . . . . . . . . . . . . . . . . . .  14
     A.3.  Post-conditions . . . . . . . . . . . . . . . . . . . . .  17
   Appendix B.  Service Flows of 6G System Assisted AI Agent
           Service . . . . . . . . . . . . . . . . . . . . . . . . .  17
     B.1.  Pre-conditions  . . . . . . . . . . . . . . . . . . . . .  17
     B.2.  Service Flows . . . . . . . . . . . . . . . . . . . . . .  18
     B.3.  Post-conditions . . . . . . . . . . . . . . . . . . . . .  18
   Appendix C.  Service Flows of Collaborative AI Agents . . . . . .  19
     C.1.  Pre-conditions  . . . . . . . . . . . . . . . . . . . . .  19
     C.2.  Service Flows . . . . . . . . . . . . . . . . . . . . . .  19



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     C.3.  Post-conditions . . . . . . . . . . . . . . . . . . . . .  20
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .  20

1.  Introduction

   AI Agent can do some work instead of people leveraging the ability of
   LLM (Large Language Model).  Every Agent may have different
   abilities, and sometimes they need to cooperation to complete a task.
   During the task process, they need to communicate with each other.
   Nowadays, communication methods among the AI Agents across domains
   are still an open issue.  This document mainly focuses on the AI
   Agent communications across domains or among different organizations.

   The AI Agents mentioned in this document include the software ones
   and the embodied robot ones.  Examples of the first software mode
   include the AI assistants on mobile phones, and the AI Agent services
   provided on Internet by different organizations.  For the second
   embodied robot mode, the Agent may or may not have a SIM (Subscriber
   Identity Module) distributed by the 3GPP operators for identifying
   itself and authentication.

   In the section 6.6 to 6.8 of [TR22.870], which is still under
   working, some use cases and requirements of AI Agent communication
   from the 6G aspect are introduced.  It proposes that some
   standardization work may be needed for supporting interoperability.

   This document reviews the 6G AI Agent use cases, and discusses the
   potential work to enable the Agent Communication Network (ACN).  A
   referred analysis can be found in [I-D.rosenberg-ai-protocols], in
   which some use cases and requirements for AI Agent protocols are
   introduced.  Meanwhile, a framework is also described for the agent
   communications in that draft, and it includes the communications
   between AI agent and User, AI agent and API, AI agent and AI agent.
   By comparison, this document would mainly talk about the Agent to
   Agent (A2A) communications, and explore potential frameworks more
   detailedly.

2.  Use Case on AI-agents Communication


2.1.  Grouping During Task Process

   Grandpa Bob plans to clean the room and host a gathering at home with
   his daughter Alice's family and his son Charlie's family.  So, he
   issued the command "Clean the room and help me prepare for the family
   gathering tomorrow afternoon" to his AI-assistant.  The detailed
   service flows can be found in Appendix A.




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      ..............................  ..................................
      .  Single User Group1        .  .  Food Delivery APP Group4      .
      .                            .  .                +---------+     .
      .                            .  .  +---------+   |         |     .
      .                            .  .  |FoodCom's|   |  Drone  |     .
      .                     +------.--.--+   AI    |   |         |     .
      .                     |      .  .  |Assistant|   +---------+     .
      . +---------+    +----+----+ .  .  +---------+                   .
      . |         |    |  Bob's  | .  ..................................
      . |   Bob   +----+    AI   +-.---------------------------+
      . |         |    |Assistant+-.----------+                |
      . +---------+    +--+-+----+ .          |                |
      .                   | |      .  ................  ................
      .      +------------+ |      .  . Single       .  .  Single      .
      .      |              |      .  . User Group2  .  .  User Group3 .
      . +----+----+    +----+----+ .  . +---------+  .  . +---------+  .
      . |  Home   |    |  Self   | .  . | Alice's |  .  . |Charlie's|  .
      . | Cleaning|    | Driving | .  . |   AI    |  .  . |   AI    |  .
      . |  Robot  |    |   Car   | .  . |Assistant|  .  . |Assistant|  .
      . +---------+    +---------+ .  . +---------+  .  . +---------+  .
      ..............................  ................  ................

   Figure 1: Static and Temp Grouping in Agent Communication Network


   As shown in Figure 1 for this use case, we have four groups
   relatively static, i.e., the Group 1 to 4.  Meanwhile, some temp
   groups are also needed in the service flows.

   1.  Bob's AI assistant needs to check the schedule of relatives, so a
       group including the AI assistants of Bob, Alice, and Charlie
       needs to be formed.

   2.  Bob's AI assistant and the food company's Agent need to form a
       group for discussing the food delivery location and time.

   3.  To delivery the food, the drone of the food company may visit
       Bob's house, and some A2A communications within a temp group may
       be needed.

   4.  The self driving car may need to go to the houses of Alice and
       Charlie to pick them up, and some A2A communications within a
       temp group may be needed.








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2.2.  Potential Requirements for ACN

   To fulfill the task, the AI agent should be able to understand the
   user's intent and make a plan containing some task-oriented actions
   for the task.  To enable the cooperation, each agent should have an
   ID and some characteristics, which should be visible in the Agent
   Communication Network (ACN).  For the ACN, it needs to support the
   following requirements.

   1.  The ACN should support communications of AI Agents from different
       domains, and communications among the AI Agents need to be
       secured.

   2.  The ACN should support the discovery of AI Agents with specific
       skills for a task.

   3.  The ACN should support the flexible grouping of the task-related
       Agents, even when the Agents are from different domains.

   4.  The ACN should support the authentication and authorization of
       the AI Agents, when forming a temp group for a task.

   5.  The ACN should be aware of the roles, relationships, and
       permissions of the Agents in a task group.


3.  Use Case on 6G System Assisted AI Agent Service


3.1.  Assistance of Network

   Due to the limited ability of an AI Agent on device.  It is expected
   that the 6G system can assist AI agent device for awareness, decision
   making and actions in a couple of aspects.  Detailed service flows of
   this use case can be found in Appendix B.

   In the aspect of providing external environment information, 6G
   system can provide the sensing information to the Agent.  For
   example, the information surrounding objects is useful for a vehicle
   to realize the traffic situation in real time, and based on which the
   vehicle can do the corresponding actions such as changing lane and
   speed.  Additional, 6G system can provide the real time QoS change
   information.  For example, this planed QoS information can be used
   for vehicle to change autonomous mode to manual mode when the QoS
   cannot fulfill the expected latency.






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   In the aspect of providing computing, 6G system can provide a more
   powerful AGI (Artificial General Intelligence) model than the light-
   weight one on the Agent.  Thus, task offloading will be needed to
   realize a "device-network collaboration", in order to make a suitable
   decision and action.  By doing so, 6G network needs to provide some
   3GPP services (e.g. sensing, positioning, text-voice converting,
   language translation) from 6G network.



3.2.  Potential Requirements for ACN

   To fulfill a task, the AI agent should be able to communicate with
   the 6G system to obtain environment information, computing service,
   etc.  For the ACN, it needs to support the following requirements.

   1.  The ACN should support exposing its services and tools to the
       Agents for invoking.

   2.  The ACN should support real time communications between the Agent
       on device and the service point on the ACN, if needed.

   3.  The ACN should be able to monitor the performance of the service,
       and report to the control point if service degeneration happens.
       The control point can be in the Agent or within the ACN.

   4.  The ACN should be aware of the network status and be able to
       expose the network information to the Agent.  Here, the network
       condition can be regarded as one of the environment information.

   5.  The ACN should be aware of the different SLA requirements of
       Agent interconnections, and apply proper policies.


4.  Use Case on Collaborative AI Agents


4.1.  Collaboration of AI Agent

   An AI agent can be implemented in the network, and it can perform
   tasks representing e.g. devices, persons, drones, or cars.  By
   offloading tasks to the network, devices can save on complexity and
   energy consumption.  Furthermore, an AI Agent in the network can
   still represent a device, person, drone or car, when that device,
   person, drone or car is not reachable, e.g. because of radio
   conditions or battery outage.  Offload can happen towards a local/
   edge network but can also be to a nearby other device with more
   processing capabilities.



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   In this scenario, when the collaborating AI Agents are implemented in
   different networks, some basic functionality needs to be standardised
   to the collaboration between AI agents.  E.g. how to identify an AI
   Agent, how to authorise access to a different AI Agent and how to
   establish and maintain secure association between AI Agents.

   Detailed service flows of this use case can be found in Appendix C.


4.2.  Potential Requirements for ACN

   When the AI Agent is implemented in the network, the AI Agent
   applications need to be installed on the UE.  The ACN needs to
   support the following requirements.

   1.  The ACN should support hosting of large amounts of AI agent
       applications, and the invoking of the users.

   2.  The ACN should support the secure interoperability between AI
       Agents and between AI Agents and applications to achieve a
       collaborative task.


5.  Cooperation Layer in Agent Communication

   There are four layers to enable the Agent communication as shown in
   Figure 2.

                      +-------------------------------+
                      |          Task Layer           |
                      +-------------------------------+
                      |       Cooperation Layer       |
                      +-------------------------------+
                      |         Agent Layer           |
                      +-------------------------------+
                      |        Network Layer          |
                      +-------------------------------+

               Figure 2: Four Layers for Agent Communication

   1.  The first layer is the network layer.  It should provide the
       connection service needed between agents.

   2.  The second layer is the agent layer.  It should provide the agent
       service, and support some basic Agent to Agent communication
       functionality.





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   3.  The third layer is the cooperation layer.  It should support the
       authentication of the agents, networking of the agents for a
       task, etc.  It is the main layer focused by this document.

   4.  The task layer is the fourth layer.  The task may come from a
       user or an Agent.  Some of the tasks need the involvement of the
       cooperation layer.

   There may be various tasks and various Agents, but the number of the
   realizations of the cooperation layer should be few.  With this new
   layer, flexible networking and authorization mechanisms for Agent
   Communication can be supported.


6.  Communication Modes of ACN

   There are four types of the cooperation modes for the Agent
   Communication.  It should be noted that we are talking about the A2A
   communication across domains, which is perhaps more complicated than
   the A2A communication within a group or within an organization.































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      +------------------------------+  +------------------------------+
      | Cooperation Service in Cloud |  | Cooperation Service in Cloud |
      | +-------------------------+  |  | +-------------------------+  |
      | | Control & Data Message  |  |  | |     Control Message     |  |
      | ++--+-----------------+--++  |  | +--+--------------------+-+  |
      +--+--+-----------------+--+---+  +----+--------------------+----+
         |  |                 |  |           |                    |
         |  |                 |  |           |        Data        |
       +-+--+----+       +----+--+-+    +----+----+  Message +----+----+
       |         |       |         |    |         +----------+         |
       |  Agent1 |       |  Agent2 |    |  Agent3 |          |  Agent4 |
       |         |       |         |    |         |          |         |
       +---------+       +---------+    +---------+          +---------+
                    (a)                                (b)

                +---------+                       +---------+
                |         +----Control Message----+         |
                |  Agent5 |                       |  Agent6 |
                |         +------Data Message-----+         |
                +---------+                       +---------+
                                    (c)

       ............................       ..............  ..............
       .       Agent Group1       .       .   Agent    .  .   Agent    .
       .                          .       .   Group2   .  .   Group3   .
       ............................       ..............  ..............
                    |                          |              |
        +-----------+-------------+       +----+--------------+-----+
        |     Agent Gateway1      |-------|      Agent Gateway2     |
        +-----------+-------------+\     /+-----------+-------------+
                    |                \ /              |
                    |                / \              |
        +-----------+-------------+/     \+-----------+-------------+
        |     Agent Gateway3      |-------|     Agent Gateway4      |
        ++--+-----------------+--++       +--+--------------------+-+
         |  |                 |  |           |                    |
       +-+--+----+       +----+--+-+    +----+----+          +----+----+
       |         |       |         |    |         |          |         |
       |  Agent7 |       |  Agent8 |    |  Agent9 +----------+ Agent10 |
       |         |       |         |    |         |          |         |
       +---------+       +---------+    +---------+          +---------+
                                    (d)

           Figure 3: Four Types of Agent Communication Modes

   1.  In the type (a), Agent1 and Agent2 connect to the service in the
       cloud firstly, for example via an installed APP.  After that,
       they can communicate by using the service in the cloud.



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   2.  In the type (b), Agent3 and Agent4 connect to the service in the
       cloud firstly, for example via an installed APP.  After that,
       they can communicate by using the service in the cloud.
       Optionally, they can establish a directly connected tunnel to
       transfer data messages.

   3.  In the type (c), where perhaps no Internet service is available,
       Agent5 and Agent6 need to authenticate each other, and establish
       a directly connected tunnel to transfer control and data
       messages.

   4.  In the type (d), Agents and Agent Groups are interconnected by
       Agent Gateways.  It is a decentralized structure.

   For the first and second mode, the Agents are connected via a
   relatively centralized way.  The advantages are that the realizations
   are easy to be extended, for example, though the APP software update.
   In Section 7, the framework and some related procedures of this mode
   is discussed.

   The third mode works like a self-organize network.  A basic
   communication channel and a common protocol are needed here.

   The Agent Gateways in the fourth mode work in a distributed way.  A
   gateway interconnection protocol is need here.  In Section 8, the
   framework and some related procedures of this mode would be talked
   about.


7.  Framework of Centralized Agent Communication Platform

   The framework of the centralized platform based Agent communication
   is shown in Figure 4.

   Some assumptions of the framework are listed as follows:

   1.  The organization A and B all have registered in the centralized
       platform P1.

   2.  The Agent A needs to fulfil a task T, which cannot be completed
       within the domain A.  Another agent with skill S is needed, and
       it is included in the centralized platform P1.

   3.  The ORG B or Agent B has registered with the skill S in the
       centralized platform P1, and Agent B supports public invocation.






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                         +-------------------------------+
                         |   Centralized Platform P1     |
                         +-------------------------------+
                                     |      |
                                     |      |
            Domain A of ORG A        |      |   Domain B of ORG B
      .............................. |      |    ..................
      . +---------+    +---------+ . |      |    .  +---------+   .
      . |         |    |         +-.-+      +----.--+         |   .
      . | User A  +----+AI Agent +-.-------------.--+AI Agent |   .
      . |         |    |    A    | .             .  |    B    |   .
      . +---------+    +-+--+----+ .             .  +----+----+   .
      .                  |  |      .             .       |        .
      .      +-----------+  |      .             .       |        .
      .      |              |      .             .       |        .
      . +----+----+    +----+----+ .             .  +----+----+   .
      . |         |    |         | .             .  |         |   .
      . | User C  |    | AI Agent| .             .  |  User B |   .
      . |         |    |    Z    | .             .  |         |   .
      . +---------+    +---------+ .             .  +---------+   .
      ..............................             ..................

      Figure 4: Centralized Platform based A2A Communication Framework

   A general procedure of the cooperation method is described as
   follows:

   1.  Agent A logs in the centralized platform P1, and searches for an
       Agent with skill S.  Agent B is found.

   2.  Platform P1 triggers the ORG B to notify the Agent B to log in
       the platform P1.

   3.  To complete the task T, Agent A and Agent B form a group to
       enable the communications between them.

   4.  After the task T is completed, Agent A can evaluate the service
       of Agent B, and the group may be deleted in the platform P1.

   Alternatively, after the trust relationship is established on the
   platform P1, Agent A and Agent B can also communicate directly.  Or,
   they can use the two paths for different kinds of data delivery.  For
   example, to transfer some files, they can use the directly connected
   tunnel, and to transfer some simple messages, they can use the
   overlay platform P1.






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   Figure 4 has shown a simple case with only two Agents to form a
   group.  If more agents are needed for the task T, a more complicated
   networking mechanism on the platform P1 can be supported.  Even the
   Agent A can delete or add some agents on the task process.

8.  Framework of Decentralized Agent Cooperation

   The framework of the gateway-based Agent communication is shown in
   Figure 5.

   Some assumptions of the framework are listed as follows:

   1.  The organization A has registered in the Gateway G1, and the
       organization B has registered in the Gateway G2.  Gateway G1 and
       G2 are in the same Agent Federation F1, which contains many agent
       gateways.

   2.  The Agent A needs to fulfil a task T, which cannot be completed
       within the domain A.  Another agent with skill S is needed, and
       it is included in the decentralized Agent Federation F1.

   3.  The ORG B or Agent B has registered with the skill S in the Agent
       Federation F1, and Agent B supports public invocation.

       +-------------------------+      +-------------------------+
       |   Agent Gateway G1      +------+   Agent Gateway G2      |
       +------------+------------+      +-------------+-----------+
                    |                                 |
      ..............................         ..................
      . +---------+    +---------+ .         .  +---------+   .
      . |         |    |         | .         .  |         |   .
      . | User A  +----+AI Agent | .         .  |AI Agent |   .
      . |         |    |    A    | .         .  |    B    |   .
      . +---------+    +-+--+----+ .         .  +----+----+   .
      .                  |  |      .         .       |        .
      .      +-----------+  |      .         .       |        .
      .      |              |      .         .       |        .
      . +----+----+    +----+----+ .         .  +----+----+   .
      . |         |    |         | .         .  |         |   .
      . | User C  |    | AI Agent| .         .  |  User B |   .
      . |         |    |    Z    | .         .  |         |   .
      . +---------+    +---------+ .         .  +---------+   .
      ..............................         ..................
            Domain A of ORG A                Domain B of ORG B

           Figure 5: Gateway-based Agent Communication Framework





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   A general procedure of the cooperation method is described as
   follows:

   1.  Agent A logs in the Gateway G1 of the Agent Federation F1, and
       searches for an active Agent with the skill S.  Agent B is found.

   2.  Gateway G1 and Gateway G2 form a temp group for the task.

   3.  To complete the task T, Agent A and Agent B in the group
       communicate by using the Gateway G1 and G2.

   4.  After the task T is completed, Agent A can evaluate the service
       of Agent B, and the group may be deleted.


   Figure 5 has shown a simple case with only two Agents.  If more
   agents are needed for the task T, a more complicated networking
   mechanism on the Gateways can be supported.  Even the Agent A can
   delete or add some agent on the task process.

   Some of the requirements of Gateways are introduced as follows.

   1.  Gateways should support the agent register and discovery.

   2.  Gateways should support cross-domain relays and state
       synchronizations.

   3.  Gateways should be able to notify the ACN of the information
       about the agent locally connected and related skills, and support
       the tunnel establishment for the cross domain traffic.

   4.  Gateways should support skill-based routing, where a Gateway
       works like an Agent Proxy to find the target Service Agents,
       after understanding the intent of the user or the Agent.

9.  IANA Considerations

   TBD.

10.  Security Considerations

   TBD.

11.  Acknowledgements

   TBD.

12.  References



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12.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,
              <https://www.rfc-editor.org/info/rfc2119>.

12.2.  Informative References

   [I-D.rosenberg-ai-protocols]
              Rosenberg, J. and C. F. Jennings, "Framework, Use Cases
              and Requirements for AI Agent Protocols", Work in
              Progress, Internet-Draft, draft-rosenberg-ai-protocols-00,
              5 May 2025, <https://datatracker.ietf.org/doc/html/draft-
              rosenberg-ai-protocols-00>.

   [TR22.870] 3GPP TR 22.870, "Study on 6G Use Cases and Service
              Requirements", 2025.

Appendix A.  Service Flows of AI-agents Communication


A.1.  Pre-conditions

   Some assumptions for the service flows of this use case are listed as
   follows:

   1.  Bob has just purchased a home robot and has not connected to
       Internet.

   2.  Except for the home robot that Bob just bought, all other AI
       agents of users, have been assigned with digital identities
       associated with the user's identity.

   3.  The users' AI-agents involved in this scenario include AI
       assistant, drone and intelligent vehicle, etc.  Intelligent
       vehicles are connected through cellular networks, while other AI-
       agents are connected through home WiFi.

   4.  All AI-agents registered to 6G system, so that their attributes
       are visible for some of the members, based on permission and
       authorization.


A.2.  Service Flows

   The service flows are described as follows:




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   1.  Bob, Alice, and Charlie each request the operator to create AI
       agent groups for them.  They then invite their respective AI
       agents, such as their AI assistants, smart cars, drones, etc., to
       join their individual groups.  In other words, there are separate
       groups for Bob, Alice, and Charlie, allowing the AI agents within
       the same group to communicate with each other.  In addition to
       owner information (e.g. related user, etc.), examples attributes
       for Bob's AI agent in this use case are as Figure 6.

   2.  The newly purchased home robot joins to Bob's group after
       authentication, and is associated with Bob's identity.  Then, the
       home robot reports its capability to the group.

   3.  Bob sends the request to his AI-assistant, and request the AI-
       assistant to arrange the gathering as task coordinator.  The AI-
       assistant received Bob's request.  Based on the local or cloud-
       based knowledge base, Bob's AI-assistant retrieves the history of
       past family gatherings, determines the list of sub tasks and
       distributes the sub tasks to corresponding AI agents.

   4.  Bob's AI-assistant communicates with the discovered cleaning
       robot based on its capabilities and sends the request to the
       cleaning robot to carry out a full house cleaning.  When the
       cleaning robot needs collaboration from other robots, e.g. to
       move some heavy furniture, it will setup a cleaning group with
       others to enable efficient communication within the cleaning
       group.  After the cleaning, the communication group will be
       released accordingly.

   5.  Bob's AI-assistant communicates with the discovered and selected
       restaurant's AI assistant by matching the requirements and AI
       agents' attributes.  Bob's AI-assistant orders food for tomorrow
       and negotiate the food delivery time and location with
       restaurant's AI assistant.  The restaurant's AI assistant selects
       a drone based on its capabilities from restaurant's group, to do
       the food delivery.  Then the restaurant's AI assistant sends the
       determined time and location to the food delivery drone and sends
       the information of selected drone to Bob's AI-assistant, so that
       Bob's AI-assistant can communicate with drone.

   6.  During food delivery, the drone offloads a portion of the
       computational tasks to the network, to assist it in obstacle
       identification, by assisting in the process of modal
       transformation, for example, by pre-processing the images
       captured by drones, and obtaining alert data.  When drones arrive
       at the pick-up point, they will setup a temporary communication
       group with the home robot to enable secure and cooperative food
       delivery.  The communication is supported even if the drone and



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       home robot transmit different modality information, e.g.  video/
       text, etc.  The communication group will be released after the
       delivery.

   7.  Bob's AI-assistant communicates with Alice's AI assistant and
       intelligent vehicle.  Bob's AI-assistant negotiates with Alice's
       AI assistant for the time and place to pick up Alice's and sends
       the request to the intelligent vehicle to pick up Alice's with
       negotiation result (i.e. the pick-up time and place).

   8.  Bob's AI-assistant communicates with Charlie's AI assistant and
       intelligent vehicle.  Bob's AI-assistant negotiates with
       Charlie's AI assistant for the time and place to pick up
       Charlie's and sends the request to the intelligent vehicle to
       pick up Charlie's with negotiation result (i.e. the pick-up time
       and place).

+-----------+-------------------+------------------+-------------------+
|           | Service Features  |   Capabilities   |    Permission     |
+-----------+-------------------+------------------+-------------------+
| AI        | 1)Service         | 1)WiFi & cellular| InvitationAllowed:|
| assistant |   description:    |   connection;    |  true;            |
|           |   Voice and       | 2)Tools          | DiscoveryAllowed: |
|           |   Text-Based      |   (Perception +  |  true;            |
|           |   Interaction,    |   Action);       | ShareAllowed:     |
|           |   Information     | 3)Reasoning &    |  true;            |
|           |   Retrieval,      |   Decision       | CreatGroupAllowed:|
|           |   Personalized    |   making;        |  true             |
|           |   Recommendations | 4)Memory +       |                   |
|           | 2)Service area:   |   Reflection     |                   |
|           |   Wide            |                  |                   |
|           | 3)Moving speed:   |                  |                   |
|           |   N/A             |                  |                   |
+-----------+-------------------+------------------+-------------------+
| Drone     | 1)Service         | 1)WiFi & cellular| InvitationAllowed:|
|           |   description:    |   & V2V          |  true;            |
|           |   e.g. Radar,     |   connection;    | DiscoveryAllowed: |
|           |   Camera,         | 2)Tools          |  true;            |
|           |   Grasping,       |   (Perception +  | ShareAllowed:     |
|           |   Navigation      |   Action)        |  true;            |
|           | 2)Service area:   |                  | CreatGroupAllowed:|
|           |   Wide            |                  |  true             |
|           | 3)Moving speed:   |                  |                   |
|           |   Medium          |                  |                   |
+-----------+-------------------+------------------+-------------------+
|Intelligent| 1)Service         | 1)WiFi & cellular| InvitationAllowed:|
| vehicle   |   description:    |   connection;    |  true;            |
|           |   e.g. Radar,     | 2)Tools          | DiscoveryAllowed: |



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|           |   Camera, Driver  |   (Perception +  |  true;            |
|           |   Assistance, and |   Action);       | ShareAllowed:     |
|           |   improved        | 3)Reasoning &    |  true;            |
|           |   Navigation      |   Decision       | CreatGroupAllowed:|
|           | 2)Service area:   |   making;        |  false            |
|           |   Wide            | 4)Sensing        |                   |
|           | 3)Moving speed:   |                  |                   |
|           |   High            |                  |                   |
+-----------+-------------------+------------------+-------------------+
| Home      | 1)Service         | 1)WiFi           | InvitationAllowed:|
| robot     |   description:    |   connection;    |  true;            |
|           |   e.g. Voice      | 2)Tools          | DiscoveryAllowed: |
|           |   interaction,    |   (Perception +  |  true;            |
|           |   Cleaning,       |   Action)        | ShareAllowed:     |
|           |   Security        |                  |  true;            |
|           |   Monitoring,     |                  | CreatGroupAllowed:|
|           | 2)Service area:   |                  |  true             |
|           |   Local           |                  |                   |
|           | 3)Moving speed:   |                  |                   |
|           |   Low             |                  |                   |
+-----------+-------------------+------------------+-------------------+

            Figure 6: Illustrative attributes of AI agents

A.3.  Post-conditions

   The expected results are listed as follows:

   1.  The cleaning robot cleans Bob's house.

   2.  The drone sends the foods from the restaurant to Bob's house.

   3.  The intelligent vehicle picks up Alice's and Charlie's and sends
       them to Bob's house.

   4.  Alice, Charlie and Bob have a happy gathering party.


Appendix B.  Service Flows of 6G System Assisted AI Agent Service


B.1.  Pre-conditions

   Some assumptions for the service flows of this use case are as
   follows.






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   Bob has a robot nanny as his personal AI agent, bought from vendor-A.
   Bob's cell phone is his another personal AI agent bought from vendor-
   B.  Those AI agents on device, as personal assistant, can assist Bob
   with suggestions and actions based on information the AI agents are
   aware of.


B.2.  Service Flows

   The service flows are described as follows:

   1.  Bob, living in his home in Beijing, decided to go to Sanya for
       his winter vacation.  He asked his robot nanny (AI agent) to book
       a 5-star hotel with lowest price.

   2.  The personal assistant began to check the well-known brand hotels
       in Sanya.  As Bob is a VIP in some hotels and the AI agent needs
       to get the VIP price, when the robot nanny tried to login the
       hotel website, the application checked with 6G network that the
       AI agent (Robot nanny) is Bob's valid personal device and the
       application provided the VIP price to the Robot nanny.

   3.  By collecting a couple of 5-star hotels' price, the Robot nanny
       finally selected and booked a hotel room with the lowest price
       for Bob.

   4.  Later-on, when Bob has left home to the airport, he remembers
       there is a delivery at home that need to pick up.  Thus Bob asked
       the AI agent on cell phone, via 6G network, to notify robot nanny
       who is at home to pick up the delivery.  Given the two AI agents
       are from different vendors, they support different protocols and
       information modalities, the 6G network helped to interconnect the
       cell-phone agent with the robot nanny and then transform the
       "pick-up delivery" command from the cell phone to the pictures
       with guideline marks that the robot nanny can parse.

   5.  Robot nanny managed to pick up the delivery.


B.3.  Post-conditions

   The expected results are listed as follows.  Thanks to the 6G
   network, the AI agent on device can assist Bob to find the VIP price
   for booking hotel, and the AI agents can communicate with each other
   without "language" barrier.






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Appendix C.  Service Flows of Collaborative AI Agents


C.1.  Pre-conditions

   Some assumptions for the service flows of this use case are as
   follows.

   Husband and wife John and Ann own an electric car.  The electric car
   has an AI Agent that can organise various things for the car.  This
   includes that it can communicate with applications from the energy
   grid to optimise charging the car.  There is a "spot-price" for
   electricity that fluctuates with locally available electricity.  The
   price can even be negative if there is more renewable energy is
   produced than can be used.  The intelligent agent for the car is
   provided by the car company.  The local networks the AI Agent runs on
   are determined by contracts the car company has.

   John has a personal AI Agent that amongst others manages his
   calendar.  John gets the subscription for the AI Agent through his
   corporate employer.

   Also, Ann has a personal AI Agent that manages her calendar.  As Ann
   is a self-employed consultant, she obtains a subscription for her
   personal AI Agent from her telecommunications provider.

   The car AI Agent has been authorised by John and Ann to access their
   personal AI Agents to obtain information about their calendars.

C.2.  Service Flows

   The service flows are described as follows:

   1.  John is on a business trip abroad with his car.  While he is
       asleep in a hotel, the car is connected to a charger.  The AI
       Agent for the car runs in an edge network near the car.

   2.  The car AI Agent communicates with a local application for the
       local energy grid and notices that the price for electricity is
       particularly high that night in the area of the hotel.  There is
       the possibility to make a profit if the car can actually provide
       energy from its battery back to the grid.

   3.  To determine whether it is a good idea to provide energy from the
       car battery back to the grid, the car AI Agent needs to check
       whether the car needs to travel far next day.  Rather than
       calling John and Ann, and waking them up, to get that
       information, the AI Agent checks the AI Agents from John and Ann



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       to see if any large trips are planned.  The AI Agent for John has
       ported to an edge location at the hotel.  The AI Agent for Ann
       runs in her telecommunications network back at home.

   4.  The personal AI Agent from John indicates that the next day John
       plans to travel back home, a 900 km journey.  It is not a good
       idea to use the car battery to sell energy back to the grid.

   5.  In the morning, John sees a message from a friend asking him to
       meet some friends in the pub.  The friends (or their personal AI
       Agents) are not authorised to access calendar information from
       his AI Agent.


C.3.  Post-conditions

   The expected results are listed as follows.  Information was
   exchanged between the car AI Agent and the personal AI Agents from
   John and Ann, even though these AI Agents at that time used computing
   resources from different providers in different countries.
   Information was protected against unauthorised access.



Author's Address

   Zongpeng Du
   China Mobile
   No.32 XuanWuMen West Street
   Beijing
   100053
   China
   Email: duzongpeng@foxmail.com


















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