AI Orchestrator Agent for Telecommunications Intent Routing
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Solution Overview
Problem
Conventional artificial intelligence systems in telecommunications face challenges such as 'catastrophic forgetting' and lack of effective integration pathways for new skill agents, limited usability for inexperienced users, and inadequate multi-tiered access control, leading to suboptimal performance and security issues.
Innovation Solution
An AI system comprising multiple specialized skill agents coordinated by an orchestrator agent, which uses intent mapping neural networks and reinforcement learning to determine user intents, deploy new agents alongside existing ones, and enforce multi-tiered access control, enabling effective action execution and secure data access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single AI agent is trained to perform multiple different actions in a telecommunications system, then the system can handle diverse user intents, but the agent experiences catastrophic forgetting and performance degradation
Solution Approach 1:
The system divides a single multi-functional AI agent into multiple specialized skill agents, each trained to perform specific actions (e.g., troubleshooting, provisioning, billing). The orchestrator agent coordinates these specialized agents based on user intent, allowing the system to handle diverse intents without any single agent experiencing catastrophic forgetting.
2Adaptability or versatility
If the system deploys new skill agents to expand functionality, then the system can perform additional actions, but there is no effective integration pathway for new agents
Solution Approach 1:
The orchestrator agent serves as a universal coordination layer that manages multiple skill agents with different functionalities. It receives user inputs, determines intent, identifies appropriate skill agents, and routes tasks accordingly. This universal interface simplifies the integration of new skill agents, as they only need to communicate with the orchestrator through standardized mechanisms.
Solution Approach 2:
The system implements feedback loops where skill agents report their capabilities and performance to the orchestrator, and the orchestrator adjusts task allocation based on this feedback. This enables dynamic integration of new skill agents without requiring complex reconfiguration of the entire system.
3Productivity
If the system processes complex user inputs requiring multiple actions, then it can fulfill comprehensive user intents, but determining the correct sequence of actions becomes difficult
Solution Approach 1:
The orchestrator agent dynamically determines the sequence of actions based on the specific user intent and the capabilities of available skill agents. Rather than following a fixed sequence, the system adapts the action order dynamically, selecting and coordinating skill agents in the optimal sequence for each unique user request.
4Productivity
If the system allows broad access to AI skill agents for operational efficiency, then user intents can be fulfilled quickly, but security and access control become inadequate
Solution Approach 1:
The system implements multi-tiered access control where different skill agents have different access levels and permissions tailored to their specific functions. The orchestrator agent checks access control conditions locally for each task, granting appropriate access rights based on the user's role and the sensitive nature of the operation, rather than applying a uniform access policy across all agents.
Data Source
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AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an artificial intelligence system. In one aspect, a system includes multiple artificial intelligence skill agents that have each been trained to perform different actions in a telecommunications system. The system also includes an orchestrator agent that interacts with each of the artificial intelligence skill agents and coordinates which of the artificial intelligence agents performs actions in response to user inputs. The orchestrator agent receives a user input and determines an intent expressed by the user input. The orchestrator agent transmits an instruction to an artificial intelligence skill agent to perform an action that provides a response to the intent. In response to receiving the instruction from the orchestrator agent, the artificial intelligence skill agent performs the action when the artificial intelligence skill agent is capable of carrying out the action.