Approaches for Dialog Management in Conversational Agents
Open accessAbstract
Dialog agents, like digital assistants and automated chat interfaces (e.g., chatbots), are becoming more and more popular as users adapt to conversing with their devices as they do with humans. In this paper, we present approaches and available tools for dialog management (DM), a component of dialog agents that handles dialog context and decides the next action for the agent to take. In this paper, we establish an overview of the field of DM, compare approaches and state-of-the-art tools in industry and research work on a set of dimensions, and identify directions for further research work.
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Understanding the context of conversations is of utmost importance to create natural, believable interactions between intelligent virtual assistants and humans.
“To create natural, believable interactions between intelligent virtual assistants and humans, understanding the context of conversations is of utmost importance (Harms et al., 2018).”
From Robotic Telemedicine for Mental Health: A Multimodal Approach to Improve Human-Robot Engagement (2021) · cites this paper as Harms et al., 2018
This is a common drawback of existing dialogue systems.
“This is a common drawback of existing dialogue systems (Fitzpatrick et al., 2017; Harms et al., 2018).”
From Robotic Telemedicine for Mental Health: A Multimodal Approach to Improve Human-Robot Engagement (2021) · cites this paper as Harms et al., 2018
Great efforts are being made in this promising research field to create natural 'human-like' conversations, including the exploration of conversational robots and voice-based systems for supporting cognitive impaired individuals.
“Nevertheless, great efforts are being made in this promising research field to create natural ‘human-like’ conversations (Harms et al., 2018; Griol et al., 2019) 6 , including the exploration of conversational robots and voice-based systems for supporting cognitive impaired individuals (Cruz-Sandoval et al., 2020; Pou-Prom et al., 2020; Salichs et al., 2020).”
From Robotic Telemedicine for Mental Health: A Multimodal Approach to Improve Human-Robot Engagement (2021) · cites this paper as Harms et al., 2018
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ELIZA — a computer program for the study of natural language communication between man and machine
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Dialogue manager domain adaptation using Gaussian process reinforcement learning
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Følstad, A., Araujo, T., Law, E. L.-C., Brandtzaeg, P. B., Papadopoulos, S., Reis, L., Baez, M., Laban, G., McAllister, P., Ischen, C., et al. (2021) · Computing · doi:10.1007/s00607-021-01016-7 · Cited by 247 · see citing works
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Robotic Telemedicine for Mental Health: A Multimodal Approach to Improve Human-Robot Engagement
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Predicting Interaction Quality Aspects Using Level-Based Scores for Conversational Agents
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- Authors
- Harms, J.-G., Kucherbaev, P., Bozzon, A., & Houben, G.-J.
- Affiliations
- Delft University of Technology (NL)
- ORCID
- Bozzon, Alessandro
- Venue
- IEEE Internet Computing
- Published
- 2019-03-01
- Volume
- 23
- Issue
- 2
- Pages
- 13-22
- ISSN
- 1089-7801 (ISSN-L)
- 1941-0131
- OpenAlex
- W2901591336
- Cited by
- 78
- References
- 14
- Citations by year
- 2025: 4 · 2024: 13 · 2023: 8 · 2022: 21 · 2021: 17 · 2020: 13 · 2019: 2
- FWCI
- 4.48
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- IEEE Internet Computing (publishedVersion)
- Research Repository (Delft University of Technology) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Amsterdam Institute for Advanced Metropolitan Solutions
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- dialogue management, dialogue agents, chatbots, virtual assistants
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