Call centers, in which human operators attend clients using textual chat, are very common in modern e-commerce. Training enough skilled operators who are able to provide good service is a challenge. We propose a methodology for the development of an assisting agent that provides online advice to operators while they attend clients. The agent is easy-to-build and can be introduced to new domains without major effort in design, training and organizing structured knowledge of the professional discipline. We demonstrate the applicability of the system in an experiment that realizes its full life-cycle on a specific domain, and analyze its capabilities.
|Title of host publication||International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022|
|Publisher||International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)|
|Number of pages||3|
|State||Published - 2022|
|Event||21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022 - Auckland, Virtual, New Zealand|
Duration: 9 May 2022 → 13 May 2022
|Name||Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS|
|Conference||21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022|
|Period||9/05/22 → 13/05/22|
Bibliographical noteFunding Information:
Disclaimer: This paper was prepared for informational purposes by the Artificial Intelligence Research group of J.P. Morgan Chase & Co. and its affiliates (“J.P. Morgan”), and is not a product of the Research Department of J.P. Morgan. J.P. Morgan makes no representation and warranty whatsoever and disclaims all liability, for the completeness, accuracy or reliability of the information contained herein. This document is not intended as investment research or investment advice, or a recommendation, offer or solicitation for the purchase or sale of any security, financial instrument, financial product or service, or to be used in any way for evaluating the merits of participating in any transaction, and shall not constitute a solicitation under any jurisdiction or to any person, if such solicitation under such jurisdiction or to such person would be unlawful.
© 2022 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
- Human study
- advising agent
- call center
- human-agent interaction