AI Multi-Agent Interoperability Extension for Managing Multiparty Conversations
read the original abstract
This paper presents a novel extension to the existing Multi-Agent Interoperability specifications of the Open Voice Interoperability Initiative (originally also known as OVON from the Open Voice Network). This extension enables AI agents developed with different technologies to communicate using a universal, natural language-based API or NLP-based standard APIs. Focusing on the management of multiparty AI conversations, this work introduces new concepts such as the Convener Agent, Floor-Shared Conversational Space, Floor Manager, Multi-Conversant Support, and mechanisms for handling Interruptions and Uninvited Agents. Additionally, it explores the Convener's role as a message relay and controller of participant interactions, enhancing both scalability and security. These advancements are crucial for ensuring smooth, efficient, and secure interactions in scenarios where multiple AI agents need to collaborate, debate, or contribute to a discussion. The paper elaborates on these concepts and provides practical examples, illustrating their implementation within the conversation envelope structure.
This paper has not been read by Pith yet.
Forward citations
Cited by 1 Pith paper
-
Hallucination Mitigation with Agentic AI, Nested Learning, and AI Sustainability via Semantic Caching
Three-stage agentic review pipeline with semantic caching reduces Total Hallucination Score by 31-36% and LLM calls by 47% on a custom 310-prompt benchmark.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.