Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects
share announcement

Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 December 2024 | Viewed by 3549

Special Issue Editors

Dr. António Correia

E-Mail Website
Guest Editor
Faculty of Information Technology, University of Jyväskylä, FI-40014 Jyväskylä, Finland
Interests: artificial intelligence; complex systems; computer supported cooperative work; human-AI interaction; hybrid intelligent systems; scientometrics; social computing; science and technology studies
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Daniel Schneider

E-Mail Website
Guest Editor
Postgraduate Program in Informatics (PPGI), Federal University of Rio de Janeiro, Rio de Janeiro 21941-916, Brazil
Interests: computer supported cooperative work; crowdsourcing; digital nomadism; human-computer interaction; social computing; social media
Special Issues, Collections and Topics in MDPI journals
Dr. Benjamim Fonseca

E-Mail Website
Guest Editor
INESC TEC, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
Interests: collaborative learning; computational thinking; computer supported cooperative work; human-computer interaction; optimization; reinforcement learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Tommi Kärkkäinen

E-Mail Website
Guest Editor
Faculty of Information Technology, University of Jyväskylä, FI-40014 Jyväskylä, Finland
Interests: artificial intelligence; data mining; deep learning; educational technology; learning analytics; machine learning; neural networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Human-Artificial Intelligence (AI) interaction is on the brink of revolutionizing the world in the coming decades, transforming everything from business operations to household applications. AI empowers systems with the ability to learn, adapt, and make decisions, bringing significant benefits to fields such as medicine, architecture, education, agriculture, and forensics. This transformative technology has redefined the way we interact with the world around us, ushering in a new era of human-AI partnerships where humans use AI-infused systems both implicitly and explicitly to augment their experiences and achieve greater outcomes based on their generative capacity and contextualized meanings in practical uses.

This special issue aims to present the latest advances and perspectives in the area of human-AI interaction. Articles accepted for publication must address topics related to the design, development and evaluation of human-AI interactive systems. We invite both researchers and practitioners to contribute their high-quality original research, reviews, insights, and perspectives on these topics to this special issue.

Topics of interest include but are not limited to:

  • AI models: AI models used for human-AI interaction, such as conversational agents, recommendation systems, and assisted learning systems.
  • User interfaces: user interfaces for human-AI interaction systems, such as natural interfaces, graphical interfaces, and virtual reality-based interfaces.
  • Evaluation of human-AI interactive systems: fieldwork studies (e.g., ethnographically-informed approaches to AI system design) and methods for evaluating human-AI interactive systems such as usability assessment scales, accessibility compliance instruments, and impact assessment methodologies.
  • Challenges and opportunities of human-AI interaction in real-world settings: potential obstacles and possibilities to implementing human-AI systems in specific application domains, such as collaborative clinical work, digital well-being, misinformation, creativity work, and entertainment.

Dr. António Correia
Dr. Daniel Schneider
Prof.Dr. Benjamim Fonseca
Prof.Dr. Tommi Kärkkäinen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • foundation models
  • human-AI interaction
  • human-centered generative AI
  • hybrid intelligent systems
  • large language models
  • machine learning
  • mixed-initiative systems
  • user experience

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

21 pages, 5048 KiB  
Article
Open-Source Robotic Study Companion with Multimodal Human–Robot Interaction to Improve the Learning Experience of University Students
by Farnaz Baksh, Matevž Borjan Zorec and Karl Kruusamäe
Appl. Sci. 2024, 14(13), 5644; https://doi.org/10.3390/app14135644 - 28 Jun 2024
Viewed by 1078
Abstract
Remote, online learning provides opportunities for flexible, accessible, and personalised education, regardless of geographical boundaries. This study mode also promises to democratise education, making it more adaptable to individual learning styles. However, transitioning to this digital paradigm also brings challenges, including issues related [...] Read more.
Remote, online learning provides opportunities for flexible, accessible, and personalised education, regardless of geographical boundaries. This study mode also promises to democratise education, making it more adaptable to individual learning styles. However, transitioning to this digital paradigm also brings challenges, including issues related to students’ mental health and motivation and communication barriers. Integrating social robots into this evolving educational landscape presents an effective approach to enhancing student support and engagement. In this article, we focus on the potential of social robots in higher education, identifying a significant gap in the educational technology landscape that could be filled by open-source learning robots tailored to university students’ needs. To bridge this gap, we introduce the Robotic Study Companion (RSC), a customisable, open-source social robot developed with cost-effective off-the-shelf parts. Designed to provide an interactive and multimodal learning experience, the RSC aims to enhance student engagement and success in their studies. This paper documents the development of the RSC, from establishing literature-based requirements to detailing the design process and build instructions. As an open development platform, the RSC offers a solution to current educational challenges and lays the groundwork for personalised, interactive, and affordable AI-enabled robotic companions. Full article
(This article belongs to the Special Issue Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects)
►▼ Show Figures

Figure 1

21 pages, 2022 KiB  
Article
An Intelligent Human–Machine Interface Architecture for Long-Term Remote Robot Handling in Fusion Reactor Environments
by Tamara Benito and Antonio Barrientos
Appl. Sci. 2024, 14(11), 4814; https://doi.org/10.3390/app14114814 - 2 Jun 2024
Viewed by 624
Abstract
This paper addresses the intricate challenge posed by remote handling (RH) operations in facilities with operational lifespans surpassing 30 years. The extended RH task horizon necessitates a forward-looking strategy to accommodate the continuous evolution of RH equipment. Confronted with diverse and evolving hardware [...] Read more.
This paper addresses the intricate challenge posed by remote handling (RH) operations in facilities with operational lifespans surpassing 30 years. The extended RH task horizon necessitates a forward-looking strategy to accommodate the continuous evolution of RH equipment. Confronted with diverse and evolving hardware interfaces, a critical requirement emerges for a flexible and adaptive software architecture based on changing situations and past experiences. The paper explores the inherent challenges associated with sustaining and upgrading RH equipment within an extended operational context. In response to this challenge, a groundbreaking, flexible, and maintainable human–machine interface (HMI) architecture named MAMIC is designed, guaranteeing seamless integration with a diverse range of RH equipment developed over the years. Embracing a modular and extensible design, the MAMIC architecture facilitates the effortless incorporation of new equipment without compromising system integrity. Moreover, by adopting this approach, nuclear facilities can proactively steer the evolution of RH equipment, guaranteeing sustained performance and compliance throughout the extended operational lifecycle. The proposed adaptive architecture provides a scalable and future-proof solution, addressing the dynamic landscape of remote handling technology for decades. Full article
(This article belongs to the Special Issue Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects)
►▼ Show Figures

Figure 1

19 pages, 11964 KiB  
Article
Translating Words to Worlds: Zero-Shot Synthesis of 3D Terrain from Textual Descriptions Using Large Language Models
by Guangzi Zhang, Lizhe Chen, Yu Zhang, Yan Liu, Yuyao Ge and Xingquan Cai
Appl. Sci. 2024, 14(8), 3257; https://doi.org/10.3390/app14083257 - 12 Apr 2024
Viewed by 760
Abstract
The current research on text-guided 3D synthesis predominantly utilizes complex diffusion models, posing significant challenges in tasks like terrain generation. This study ventures into the direct synthesis of text-to-3D terrain in a zero-shot fashion, circumventing the need for diffusion models. By exploiting the [...] Read more.
The current research on text-guided 3D synthesis predominantly utilizes complex diffusion models, posing significant challenges in tasks like terrain generation. This study ventures into the direct synthesis of text-to-3D terrain in a zero-shot fashion, circumventing the need for diffusion models. By exploiting the large language model’s inherent spatial awareness, we innovatively formulate a method to update existing 3D models through text, thereby enhancing their accuracy. Specifically, we introduce a Gaussian–Voronoi map data structure that converts simplistic map summaries into detailed terrain heightmaps. Employing a chain-of-thought behavior tree approach, which combines action chains and thought trees, the model is guided to analyze a variety of textual inputs and extract relevant terrain data, effectively bridging the gap between textual descriptions and 3D models. Furthermore, we develop a text–terrain re-editing technique utilizing multiagent reasoning, allowing for the dynamic update of the terrain’s representational structure. Our experimental results indicate that this method proficiently interprets the spatial information embedded in the text and generates controllable 3D terrains with superior visual quality. Full article
(This article belongs to the Special Issue Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop