Human-Centered Artificial Intelligence

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 2964

Special Issue Editor


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Guest Editor
Department of Computer Science, Pontificia Universidad Católica de Chile, Santiago 8320000, Chile
Interests: web mining; natural language processing; human factors in AI; social media; disinformation

Special Issue Information

Dear Colleagues,

Human-centered artificial intelligence (HCAI) is an emerging discipline that places people at the center of efforts to develop AI-based systems. Its broad scope encompasses the design of new learning algorithms through to evaluating existing systems, with particular attention to the human factors involved in their development. This line of research promotes the development of algorithms, methods, metrics, and new methodologies for designing AI systems which prevent the reproduction of disparities that affect people, mitigating bias and discriminatory treatment.

This Special Issue is devoted to HCAI methods. Our aim is to disseminate the most recent advances in this discipline, promoting new methodologies to approach the human-centered design and evaluation of AI systems. The collection will include topics on new algorithms and models capable of mitigating harmful bias, model evaluation and validation methodologies, fairness evaluation metrics and systems, human-centered AI and human–computer interaction (HCI), ethics and AI, algorithmic transparency, explainability, and model interpretability.

Dr. Marcelo Mendoza
Guest Editor

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.

Dr. Marcelo Mendoza
Guest Editor

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

  • human factors in AI systems
  • HCAI and HCI
  • fairness, accountability and transparency
  • model interpretability
  • explainable artificial intelligence (XAI)
  • algorithmic transparency
  • bias mitigation
  • human-in-the-loop machine learning, reasoning, and planning
  • human-centered decision support systems

Published Papers (1 paper)

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Research

16 pages, 3607 KiB  
Article
Design of a Hyper-Casual Futsal Mobile Game Using a Machine-Learned AI Agent-Player
by Hyeyoung An and Jungyoon Kim
Appl. Sci. 2023, 13(4), 2071; https://doi.org/10.3390/app13042071 - 05 Feb 2023
Cited by 6 | Viewed by 2237
Abstract
Mobile games continue to gain popularity, and their revenues are increasing accordingly. However, due to the inherent constraints of small screen sizes and restrictions of computing, it has been considered challenging to simulate the complex gameplay of soccer games. To this end, this [...] Read more.
Mobile games continue to gain popularity, and their revenues are increasing accordingly. However, due to the inherent constraints of small screen sizes and restrictions of computing, it has been considered challenging to simulate the complex gameplay of soccer games. To this end, this paper aims to design and develop a simplified version of a five vs. five hyper-casual futsal game with only three player positions: goalkeeper, striker, and defender. It also tests a demo game to verify whether it is possible to implement an AI agent−player for each position to machine-learn and to run on a mobile device. A demo game with an AI agent−player was simulated using both PPO and SAC algorithms, and the feasibility and stability of the algorithms were compared. The results showed that each AI agent−player achieved the assigned objectives for each position and successfully machine-learned. When the algorithms were compared, the SAC algorithm showed a more stable state than the PPO algorithm when SAC directed the gameplay and interactive AI techniques. This paper shows the great potential of the application of machine-learned AI agent−players for soccer simulators on mobile platforms. Full article
(This article belongs to the Special Issue Human-Centered Artificial Intelligence)
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