A Unified Conversational Assistant Framework for Business Process Automation

• URL: http://arxiv.org/abs/2001.03543v1
• Date: Tue, 7 Jan 2020 22:30:05 GMT
• Title: A Unified Conversational Assistant Framework for Business Process Automation
• Authors: Yara Rizk, Abhishek Bhandwalder, Scott Boag, Tathagata Chakraborti, Vatche Isahagian, Yasaman Khazaeni, Falk Pollock, Merve Unuvar
• Abstract summary: Business process automation is a booming multi-billion-dollar industry that promises to remove menial tasks from workers' plates. A simple and user-friendly interface with a low learning curve is necessary to increase the adoption of such agents in banking, insurance, retail and other domains. We present a multi-agent orchestration framework to develop such proactive chatbots by discussing the types of skills that can be composed into agents and how to orchestrate these agents.
• Score: 9.818380332602622
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Business process automation is a booming multi-billion-dollar industry that promises to remove menial tasks from workers' plates -- through the introduction of autonomous agents -- and free up their time and brain power for more creative and engaging tasks. However, an essential component to the successful deployment of such autonomous agents is the ability of business users to monitor their performance and customize their execution. A simple and user-friendly interface with a low learning curve is necessary to increase the adoption of such agents in banking, insurance, retail and other domains. As a result, proactive chatbots will play a crucial role in the business automation space. Not only can they respond to users' queries and perform actions on their behalf but also initiate communication with the users to inform them of the system's behavior. This will provide business users a natural language interface to interact with, monitor and control autonomous agents. In this work, we present a multi-agent orchestration framework to develop such proactive chatbots by discussing the types of skills that can be composed into agents and how to orchestrate these agents. Two use cases on a travel preapproval business process and a loan application business process are adopted to qualitatively analyze the proposed framework based on four criteria: performance, coding overhead, scalability, and agent overlap.

Related papers

• AI Multi-Agent Interoperability Extension for Managing Multiparty Conversations [0.0]
  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.
  arXiv  Detail & Related papers  (2024-11-05T18:11:55Z)
• ReSpAct: Harmonizing Reasoning, Speaking, and Acting Towards Building Large Language Model-Based Conversational AI Agents [11.118991548784459]
  Large language model (LLM)-based agents have been increasingly used to interact with external environments. Current frameworks do not enable these agents to work with users and interact with them to align on the details of their tasks. This work introduces ReSpAct, a novel framework that combines the essential skills for building task-oriented "conversational" agents.
  arXiv  Detail & Related papers  (2024-11-01T15:57:45Z)
• 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)
• Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interface [38.76937539085164]
  This paper presents a human-centered efficient agent planning method -- Interactive Speculative Planning. We aim at enhancing the efficiency of agent planning through both system design and human-AI interaction.
  arXiv  Detail & Related papers  (2024-09-30T16:52:51Z)
• 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)
• BMW Agents -- A Framework For Task Automation Through Multi-Agent Collaboration [0.0]
  We focus on designing a flexible agent engineering framework capable of handling complex use case applications across various domains. The proposed framework provides reliability in industrial applications and presents techniques to ensure a scalable, flexible, and collaborative workflow for multiple autonomous agents.
  arXiv  Detail & Related papers  (2024-06-28T16:39:20Z)
• 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)
• Tell Me More! Towards Implicit User Intention Understanding of Language Model Driven Agents [110.25679611755962]
  Current language model-driven agents often lack mechanisms for effective user participation, which is crucial given the vagueness commonly found in user instructions. We introduce Intention-in-Interaction (IN3), a novel benchmark designed to inspect users' implicit intentions through explicit queries. We empirically train Mistral-Interact, a powerful model that proactively assesses task vagueness, inquires user intentions, and refines them into actionable goals.
  arXiv  Detail & Related papers  (2024-02-14T14:36:30Z)
• AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems [112.76941157194544]
  We propose AgentCF for simulating user-item interactions in recommender systems through agent-based collaborative filtering. We creatively consider not only users but also items as agents, and develop a collaborative learning approach that optimize both kinds of agents together. Overall, the optimized agents exhibit diverse interaction behaviors within our framework, including user-item, user-user, item-item, and collective interactions.
  arXiv  Detail & Related papers  (2023-10-13T16:37:14Z)
• 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)
• A Conversational Digital Assistant for Intelligent Process Automation [7.446834742371106]
  We explore interactive automation in the form of a conversational digital assistant. It allows business users to interact with and customize their automation solutions through natural language. We demonstrate the effectiveness of our proposed approach on a loan approval business process and a travel preapproval business process.
  arXiv  Detail & Related papers  (2020-07-27T00:38:13Z)

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.