Autonomous networks: The role of multi-agent systems

Autonomous networks: The role of multi-agent systems

£3,000.00 excl VAT

The development of agents underpinned by data and knowledge assets looks set to be a major challenge for telcos. It may take up to ten years for telcos to truly master agents, but they will be key to the realisation of fully autonomous networks.

Description

Format: PDF filePages: 25Author: Charlotte PatrickPublication Date: March 2025

 

Achieving Level 4 and 5 autonomy will see telcos crossing a chasm of complexity from the earlier intelligence and automations of Level 3. There is a need to reimagine the management of the network with new intelligence and it is not clear whether the range of currently immature technical solutions will be able to support requirements. There are a number of intricately linked problems to be solved, including:

  • Model capability
  • Large models’ inaccuracy
  • Not enough data
  • Limited observability
  • Model response too slow
  • Issues inherent in all AI/ML (e.g., bias, hallucinations, drift)
  • Explainability

Alongside a detailed overview of the challenges during the deployment of multi-agent systems (MAS), this report offers insightful recommendations to telcos seeking to embrace an intelligence architecture into their networks.

 

Table of contents

  • Executive summary
    • A distributed intelligence is desirable but challenging to implement
    • Suggested early-day actions when developing an intelligence architecture strategy
  • The journey towards an intelligence architecture providing distributed intelligence
  • The challenges of creating distributed intelligence
    • The difficulties of building a MAS and supporting it with intelligence
    • Improving the intelligence of models to enable a MAS
    • Designing and running a MAS
    • Data and knowledge: the difficulties of supporting a MAS
    • Improving data and knowledge to support a MAS
  • Summarising the barriers and the potential solutions to delivering a MAS
  • Conclusion

 

Technologies and industry terms referenced include: AI agent, automation, autonomous network, data, data mesh, decision-making, distributed intelligence, Generative AI, intelligence infrastructure, knowledge plane, large language model, LLM, Machine Learning, MAS, multi-agent systems, network autonomy, open, problem solving, sLLM, telcos, TM Forum, vendors