A coordination framework for multi-agent persuasion and adviser systems
Assistive agents have been used to give advices to the users regarding activities in daily lives. Although adviser bots are getting smarter and gaining more popularity these days they are usually developed and deployed independent from each other. When several agents operate together in the same con...
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sg-ntu-dr.10356-1426092020-06-25T05:50:42Z A coordination framework for multi-agent persuasion and adviser systems Subagdja, Budhitama Tan, Ah-Hwee Kang, Yilin School of Computer Science and Engineering ST Engineering-NTU Corporate Laboratory Engineering::Computer science and engineering Persuasive Agents Virtual Companion Assistive agents have been used to give advices to the users regarding activities in daily lives. Although adviser bots are getting smarter and gaining more popularity these days they are usually developed and deployed independent from each other. When several agents operate together in the same context, their advices may no longer be effective since they may instead overwhelm or confuse the user if not properly arranged. Only little attentions have been paid to coordinating different agents to give different advices to a user within the same environment. However, aligning the advices on-the-fly with the appropriate presentation timing at the right context still remains a great challenge. In this paper, a coordination framework for advice giving and persuasive agents is presented. Apart from preventing overwhelming messages, the adaptation enables cooperation among the agents to make their advices more impactful. In contrast to conventional models that rely on natural language contents or direct multi-modal cues to align the dialogs, the proposed framework is built to be more practical allowing the agents to actively share their observation, goals, and plans to each other. This allows them to adapt the schedules, strategies, and contents of their scheduled advices or reminders at runtime with respect to each other's objectives. Challenges and issues in multi-agent adviser systems are identified and defined in this paper supported by a survey study about perceived usefulness and user comprehensibility of advices delivered by multiple agents. The coordination among the advice giving agents are investigated and exemplified with a simulation of activity of daily living in the context of aging in place. NRF (Natl Research Foundation, S’pore) Accepted version 2020-06-25T05:50:42Z 2020-06-25T05:50:42Z 2018 Journal Article Subagdja, B., Tan, A.-H., & Kang, Y. (2019). A coordination framework for multi-agent persuasion and adviser systems. Expert Systems with Applications, 116, 31-51. doi:10.1016/j.eswa.2018.08.030 0957-4174 https://hdl.handle.net/10356/142609 10.1016/j.eswa.2018.08.030 2-s2.0-85053161394 116 31 51 en Expert Systems with Applications © 2018 Elsevier Ltd. All rights reserved. This paper was published in Expert Systems with Applications and is made available with permission of Elsevier Ltd. application/pdf |
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Engineering::Computer science and engineering Persuasive Agents Virtual Companion Subagdja, Budhitama Tan, Ah-Hwee Kang, Yilin A coordination framework for multi-agent persuasion and adviser systems |
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Assistive agents have been used to give advices to the users regarding activities in daily lives. Although adviser bots are getting smarter and gaining more popularity these days they are usually developed and deployed independent from each other. When several agents operate together in the same context, their advices may no longer be effective since they may instead overwhelm or confuse the user if not properly arranged. Only little attentions have been paid to coordinating different agents to give different advices to a user within the same environment. However, aligning the advices on-the-fly with the appropriate presentation timing at the right context still remains a great challenge. In this paper, a coordination framework for advice giving and persuasive agents is presented. Apart from preventing overwhelming messages, the adaptation enables cooperation among the agents to make their advices more impactful. In contrast to conventional models that rely on natural language contents or direct multi-modal cues to align the dialogs, the proposed framework is built to be more practical allowing the agents to actively share their observation, goals, and plans to each other. This allows them to adapt the schedules, strategies, and contents of their scheduled advices or reminders at runtime with respect to each other's objectives. Challenges and issues in multi-agent adviser systems are identified and defined in this paper supported by a survey study about perceived usefulness and user comprehensibility of advices delivered by multiple agents. The coordination among the advice giving agents are investigated and exemplified with a simulation of activity of daily living in the context of aging in place. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Subagdja, Budhitama Tan, Ah-Hwee Kang, Yilin |
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Article |
author |
Subagdja, Budhitama Tan, Ah-Hwee Kang, Yilin |
author_sort |
Subagdja, Budhitama |
title |
A coordination framework for multi-agent persuasion and adviser systems |
title_short |
A coordination framework for multi-agent persuasion and adviser systems |
title_full |
A coordination framework for multi-agent persuasion and adviser systems |
title_fullStr |
A coordination framework for multi-agent persuasion and adviser systems |
title_full_unstemmed |
A coordination framework for multi-agent persuasion and adviser systems |
title_sort |
coordination framework for multi-agent persuasion and adviser systems |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/142609 |
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1681059570998312960 |