AI Multi-Agent Interoperability Extension for Managing Multiparty Conversations
- URL: http://arxiv.org/abs/2411.05828v1
- Date: Tue, 05 Nov 2024 18:11:55 GMT
- Title: AI Multi-Agent Interoperability Extension for Managing Multiparty Conversations
- Authors: Diego Gosmar, Deborah A. Dahl, Emmett Coin, David Attwater,
- Abstract summary: This paper presents a novel extension to the existing Multi-Agent specifications of the Open Voice Initiative.
It 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.
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.
- Score: 0.0
- License:
- 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.
Related papers
- Asynchronous Tool Usage for Real-Time Agents [61.3041983544042]
We introduce asynchronous AI agents capable of parallel processing and real-time tool-use.
Our key contribution is an event-driven finite-state machine architecture for agent execution and prompting.
This work presents both a conceptual framework and practical tools for creating AI agents capable of fluid, multitasking interactions.
arXiv Detail & Related papers (2024-10-28T23:57:19Z) - A Learnable Agent Collaboration Network Framework for Personalized Multimodal AI Search Engine [14.123823081267336]
This paper proposes a novel AI Search Engine framework called the Agent Collaboration Network (ACN)
The ACN framework consists of multiple specialized agents working collaboratively, each with distinct roles such as Account Manager, Solution Strategist, Information Manager, and Content Creator.
A highlight of the ACN is the introduction of a Reflective Forward Optimization method (RFO), which supports the online synergistic adjustment among agents.
arXiv Detail & Related papers (2024-09-01T07:01:22Z) - Constraining Participation: Affordances of Feedback Features in Interfaces to Large Language Models [49.74265453289855]
Large language models (LLMs) are now accessible to anyone with a computer, a web browser, and an internet connection via browser-based interfaces.
This paper examines the affordances of interactive feedback features in ChatGPT's interface, analysing how they shape user input and participation in iteration.
arXiv Detail & Related papers (2024-08-27T13:50:37Z) - Conversational AI Multi-Agent Interoperability, Universal Open APIs for Agentic Natural Language Multimodal Communications [0.0]
This paper analyses Conversational AI multi-agent interoperability frameworks and describes the novel architecture proposed by the Open Voice initiative.
The new approach is illustrated, along with the main components, delineating the key benefits and use cases for deploying standard multi-modal AI agency (or agentic AI) communications.
arXiv Detail & Related papers (2024-07-28T09:33:55Z) - Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence [79.5316642687565]
Existing multi-agent frameworks often struggle with integrating diverse capable third-party agents.
We propose the Internet of Agents (IoA), a novel framework that addresses these limitations.
IoA introduces an agent integration protocol, an instant-messaging-like architecture design, and dynamic mechanisms for agent teaming and conversation flow control.
arXiv Detail & Related papers (2024-07-09T17:33:24Z) - Hello Again! LLM-powered Personalized Agent for Long-term Dialogue [63.65128176360345]
We introduce a model-agnostic framework, the Long-term Dialogue Agent (LD-Agent)
It incorporates three independently tunable modules dedicated to event perception, persona extraction, and response generation.
The effectiveness, generality, and cross-domain capabilities of LD-Agent are empirically demonstrated.
arXiv Detail & Related papers (2024-06-09T21:58:32Z) - AgentScope: A Flexible yet Robust Multi-Agent Platform [66.64116117163755]
AgentScope is a developer-centric multi-agent platform with message exchange as its core communication mechanism.
The abundant syntactic tools, built-in agents and service functions, user-friendly interfaces for application demonstration and utility monitor, zero-code programming workstation, and automatic prompt tuning mechanism significantly lower the barriers to both development and deployment.
arXiv Detail & Related papers (2024-02-21T04:11:28Z) - TESS: A Multi-intent Parser for Conversational Multi-Agent Systems with
Decentralized Natural Language Understanding Models [6.470108226184637]
Multi-agent systems complicate the natural language understanding of user intents.
We propose an efficient parsing and orchestration pipeline algorithm to service multi-intent utterances from the user.
arXiv Detail & Related papers (2023-12-19T03:39:23Z) - CAMEL: Communicative Agents for "Mind" Exploration of Large Language
Model Society [58.04479313658851]
This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents.
We propose a novel communicative agent framework named role-playing.
Our contributions include introducing a novel communicative agent framework, offering a scalable approach for studying the cooperative behaviors and capabilities of multi-agent systems.
arXiv Detail & Related papers (2023-03-31T01:09:00Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.