Multi-Agent AI Architectures for Automated Customer Experience Management Platforms
DOI:
https://doi.org/10.15662/IJRAI.2024.0706038Keywords:
Multi-Agent Systems (MAS), Customer Experience Management Platforms, Automated Dialogue Systems, Hierarchical Multi-Agent Architectures, Federated Multi-Agent Architectures, Conversational AI Agents, Task-Specific Intelligent Agents, Distributed Dialogue Management, Customer Interaction Automation, Human–Agent Communication Models, Context-Aware Conversation Design, Intent Recognition and Routing, Modular AI System Design, Scalable Service-Oriented Architectures, Intelligent Customer Support Systems, Agent Coordination Mechanisms, Adaptive Interaction Strategies, Enterprise Conversational Platforms, AI-Driven Customer Engagement, Complex Multi-Turn Interaction HandlingAbstract
A multi-agent approach supports more complex, realistic, and timely interaction scenarios for both customers and companies. Instead of developing monolithic dialogue systems that can support requests from any customer, multi-agent systems permit dedicated agents for specific tasks, offering richer content and handling more intricate interactions. Dialogue systems based on either hierarchical or federated multi-agent architectures are reviewed, and these two patterns are explored as foundations for customer experience management platforms in which multiple agents can automate a variety of customer interaction scenarios.
A multi-agent approach supports more complex, realistic, and timely interaction scenarios for both customers and companies. Instead of developing monolithic dialogue systems that can support requests from any customer, multi-agent systems permit dedicated agents for specific tasks, offering richer content and handling more intricate interactions. Dialogue systems based on either hierarchical or federated multi-agent architectures are reviewed, and these two patterns are explored as foundations for customer experience management platforms in which multiple agents can automate a variety of customer interaction scenarios.
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