AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can expand the Abstract, Links and BibTex record for each paper.
2024
Geurts, E.; Warson, D.; Ruiz, G. Rovelo
Boosting Motivation in Sports with Data-Driven Visualizations in VR Proceedings Article
In: ACM Int. Conf. Proc. Ser., Association for Computing Machinery, 2024, ISBN: 979-840071764-2 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Asynchronoi social interaction, Asynchronous social interaction, Cycling, Data driven, Dynamics, Extended reality, Group dynamics, Language Model, Large language model, large language models, Motivation, Natural language processing systems, Real-world, Real-world data, Social interactions, Sports, User interface, User interfaces, Virtual Reality, Visualization, Visualizations
@inproceedings{geurts_boosting_2024,
title = {Boosting Motivation in Sports with Data-Driven Visualizations in VR},
author = {E. Geurts and D. Warson and G. Rovelo Ruiz},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195387493&doi=10.1145%2f3656650.3656669&partnerID=40&md5=ec69e7abe61e572a94261ad6bbfed11c},
doi = {10.1145/3656650.3656669},
isbn = {979-840071764-2 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {ACM Int. Conf. Proc. Ser.},
publisher = {Association for Computing Machinery},
abstract = {In recent years, the integration of Artificial Intelligence (AI) has sparked revolutionary progress across diverse domains, with sports applications being no exception. At the same time, using real-world data sources, such as GPS, weather, and traffic data, offers opportunities to improve the overall user engagement and effectiveness of such applications. Despite the substantial advancements, including proven success in mobile applications, there remains an untapped potential in leveraging these technologies to boost motivation and enhance social group dynamics in Virtual Reality (VR) sports solutions. Our innovative approach focuses on harnessing the power of AI and real-world data to facilitate the design of such VR systems. To validate our methodology, we conducted an exploratory study involving 18 participants, evaluating our approach within the context of indoor VR cycling. By incorporating GPX files and omnidirectional video (real-world data), we recreated a lifelike cycling environment in which users can compete with simulated cyclists navigating a chosen (real-world) route. Considering the user's performance and interactions with other cyclists, our system employs AI-driven natural language processing tools to generate encouraging and competitive messages automatically. The outcome of our study reveals a positive impact on motivation, competition dynamics, and the perceived sense of group dynamics when using real performance data alongside automatically generated motivational messages. This underscores the potential of AI-driven enhancements in user interfaces to not only optimize performance but also foster a more engaging and supportive sports environment. © 2024 ACM.},
keywords = {Artificial intelligence, Asynchronoi social interaction, Asynchronous social interaction, Cycling, Data driven, Dynamics, Extended reality, Group dynamics, Language Model, Large language model, large language models, Motivation, Natural language processing systems, Real-world, Real-world data, Social interactions, Sports, User interface, User interfaces, Virtual Reality, Visualization, Visualizations},
pubstate = {published},
tppubtype = {inproceedings}
}
In recent years, the integration of Artificial Intelligence (AI) has sparked revolutionary progress across diverse domains, with sports applications being no exception. At the same time, using real-world data sources, such as GPS, weather, and traffic data, offers opportunities to improve the overall user engagement and effectiveness of such applications. Despite the substantial advancements, including proven success in mobile applications, there remains an untapped potential in leveraging these technologies to boost motivation and enhance social group dynamics in Virtual Reality (VR) sports solutions. Our innovative approach focuses on harnessing the power of AI and real-world data to facilitate the design of such VR systems. To validate our methodology, we conducted an exploratory study involving 18 participants, evaluating our approach within the context of indoor VR cycling. By incorporating GPX files and omnidirectional video (real-world data), we recreated a lifelike cycling environment in which users can compete with simulated cyclists navigating a chosen (real-world) route. Considering the user's performance and interactions with other cyclists, our system employs AI-driven natural language processing tools to generate encouraging and competitive messages automatically. The outcome of our study reveals a positive impact on motivation, competition dynamics, and the perceived sense of group dynamics when using real performance data alongside automatically generated motivational messages. This underscores the potential of AI-driven enhancements in user interfaces to not only optimize performance but also foster a more engaging and supportive sports environment. © 2024 ACM.
2018
Augello, Agnese; Infantino, Ignazio; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Robot Inner Perception Capability through a Soft Somatosensory System Journal Article
In: International Journal of Semantic Computing, vol. 12, no. 1, pp. 59–87, 2018, ISSN: 1793351X.
Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Cognitive Architectures, Cognitive Model, Human Robot Interaction, Motivation, Sensor systems, Somatosensory Systems
@article{augelloRobotInnerPerception2018,
title = {Robot Inner Perception Capability through a Soft Somatosensory System},
author = { Agnese Augello and Ignazio Infantino and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
doi = {10.1142/S1793351X18400044},
issn = {1793351X},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Semantic Computing},
volume = {12},
number = {1},
pages = {59--87},
abstract = {The capability of a robot being aware of its internal status is a step forward to the enhancement of human-robot interaction. The possibility of feeling either pleasant or unpleasant sensations is at the basis of the motivation level of a robot. It can modulate the "willingness" of accomplishing a given task. Negative sensations can represent an alarm indicating dangerous situations, while the feeling of a reassuring environment or a well-being sensation can be a stimulus in pursuing the task, even in the presence of a painful perception. In this paper, we illustrate a bio-inspired somatosensory system embedded in a cognitive model for a humanoid robot. The system is based on a set of soft sensors that have been designed in order to make it possible for the interpretation of the robot physical sensations through a proper classification of the perceived somatosensory signals. This interpretation triggers and modulates the motivation level of the robot as well as its behavior. textcopyright 2018 World Scientific Publishing Company.},
keywords = {Anthropomorphic Robots, Cognitive Architectures, Cognitive Model, Human Robot Interaction, Motivation, Sensor systems, Somatosensory Systems},
pubstate = {published},
tppubtype = {article}
}
The capability of a robot being aware of its internal status is a step forward to the enhancement of human-robot interaction. The possibility of feeling either pleasant or unpleasant sensations is at the basis of the motivation level of a robot. It can modulate the "willingness" of accomplishing a given task. Negative sensations can represent an alarm indicating dangerous situations, while the feeling of a reassuring environment or a well-being sensation can be a stimulus in pursuing the task, even in the presence of a painful perception. In this paper, we illustrate a bio-inspired somatosensory system embedded in a cognitive model for a humanoid robot. The system is based on a set of soft sensors that have been designed in order to make it possible for the interpretation of the robot physical sensations through a proper classification of the perceived somatosensory signals. This interpretation triggers and modulates the motivation level of the robot as well as its behavior. textcopyright 2018 World Scientific Publishing Company.
Augello, Agnese; Infantino, Ignazio; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Robot inner perception capability through a soft somatosensory system Journal Article
In: International Journal of Semantic Computing, vol. 12, no. 1, pp. 59–87, 2018, ISSN: 1793351X.
Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Cognitive Architectures, Cognitive Model, Human Robot Interaction, Motivation, Sensor systems, Somatosensory Systems
@article{augello_robot_2018,
title = {Robot inner perception capability through a soft somatosensory system},
author = {Agnese Augello and Ignazio Infantino and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051523659&doi=10.1142%2fS1793351X18400044&partnerID=40&md5=c602b9f8638911db3433de9acd74ea75},
doi = {10.1142/S1793351X18400044},
issn = {1793351X},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Semantic Computing},
volume = {12},
number = {1},
pages = {59–87},
abstract = {The capability of a robot being aware of its internal status is a step forward to the enhancement of human-robot interaction. The possibility of feeling either pleasant or unpleasant sensations is at the basis of the motivation level of a robot. It can modulate the "willingness" of accomplishing a given task. Negative sensations can represent an alarm indicating dangerous situations, while the feeling of a reassuring environment or a well-being sensation can be a stimulus in pursuing the task, even in the presence of a painful perception. In this paper, we illustrate a bio-inspired somatosensory system embedded in a cognitive model for a humanoid robot. The system is based on a set of soft sensors that have been designed in order to make it possible for the interpretation of the robot physical sensations through a proper classification of the perceived somatosensory signals. This interpretation triggers and modulates the motivation level of the robot as well as its behavior. © 2018 World Scientific Publishing Company.},
keywords = {Anthropomorphic Robots, Cognitive Architectures, Cognitive Model, Human Robot Interaction, Motivation, Sensor systems, Somatosensory Systems},
pubstate = {published},
tppubtype = {article}
}
The capability of a robot being aware of its internal status is a step forward to the enhancement of human-robot interaction. The possibility of feeling either pleasant or unpleasant sensations is at the basis of the motivation level of a robot. It can modulate the "willingness" of accomplishing a given task. Negative sensations can represent an alarm indicating dangerous situations, while the feeling of a reassuring environment or a well-being sensation can be a stimulus in pursuing the task, even in the presence of a painful perception. In this paper, we illustrate a bio-inspired somatosensory system embedded in a cognitive model for a humanoid robot. The system is based on a set of soft sensors that have been designed in order to make it possible for the interpretation of the robot physical sensations through a proper classification of the perceived somatosensory signals. This interpretation triggers and modulates the motivation level of the robot as well as its behavior. © 2018 World Scientific Publishing Company.
2014
Augello, Agnese; Infantino, Ignazio; Pilato, Giovanni; Rizzo, Riccardo; Vella, Filippo
Robotic Creativity Driven by Motivation and Semantic Analysis Proceedings Article
In: Proceedings - 2014 IEEE International Conference on Semantic Computing, ICSC 2014, pp. 285–289, IEEE Computer Society, 2014, ISBN: 978-1-4799-4002-8.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Chatbots, Cognitive Architectures, Computational Creativity, Creative Agents, Motivation, Natural Language Processing, PSI, Semantic Computing, Social Robots
@inproceedings{augelloRoboticCreativityDriven2014,
title = {Robotic Creativity Driven by Motivation and Semantic Analysis},
author = { Agnese Augello and Ignazio Infantino and Giovanni Pilato and Riccardo Rizzo and Filippo Vella},
doi = {10.1109/ICSC.2014.58},
isbn = {978-1-4799-4002-8},
year = {2014},
date = {2014-01-01},
booktitle = {Proceedings - 2014 IEEE International Conference on Semantic Computing, ICSC 2014},
pages = {285--289},
publisher = {IEEE Computer Society},
abstract = {The paper proposes a system architecture for artificial creativity that enables a robot to perform portraits. The proposed cognitive architecture is inspired by the PSI model, and it requires that the motivation of the robot in the execution of its tasks is influenced by urges. Such parameters depend on both internal and external evaluation mechanisms. The system is a premise for the development of an artificial artist able to develop a personality and a behavior that depends on its experience of successes and failures (competence), and the availability of different painting techniques (certainty). The creative execution is driven by the motivation arising from the urges, and the perception of the work being executed or performed. The external evaluation is obtained by analyzing the opinions expressed in natural language from people watching the realized portrait. textcopyright 2014 IEEE.},
keywords = {Artificial intelligence, Chatbots, Cognitive Architectures, Computational Creativity, Creative Agents, Motivation, Natural Language Processing, PSI, Semantic Computing, Social Robots},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper proposes a system architecture for artificial creativity that enables a robot to perform portraits. The proposed cognitive architecture is inspired by the PSI model, and it requires that the motivation of the robot in the execution of its tasks is influenced by urges. Such parameters depend on both internal and external evaluation mechanisms. The system is a premise for the development of an artificial artist able to develop a personality and a behavior that depends on its experience of successes and failures (competence), and the availability of different painting techniques (certainty). The creative execution is driven by the motivation arising from the urges, and the perception of the work being executed or performed. The external evaluation is obtained by analyzing the opinions expressed in natural language from people watching the realized portrait. textcopyright 2014 IEEE.
Augello, Agnese; Infantino, Ignazio; Pilato, Giovanni; Rizzo, Riccardo; Vella, Filippo
Robotic creativity driven by motivation and semantic analysis Proceedings Article
In: Proceedings - 2014 IEEE International Conference on Semantic Computing, ICSC 2014, pp. 285–289, IEEE Computer Society, 2014, ISBN: 978-1-4799-4002-8.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Chatbots, Cognitive Architectures, Computational Creativity, Creative Agents, Motivation, Natural Language Processing, PSI, Semantic Computing, Social Robots
@inproceedings{augello_robotic_2014,
title = {Robotic creativity driven by motivation and semantic analysis},
author = {Agnese Augello and Ignazio Infantino and Giovanni Pilato and Riccardo Rizzo and Filippo Vella},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906979655&doi=10.1109%2fICSC.2014.58&partnerID=40&md5=4eb7c99a7dc982f4c06c6fdaa3b0cc07},
doi = {10.1109/ICSC.2014.58},
isbn = {978-1-4799-4002-8},
year = {2014},
date = {2014-01-01},
booktitle = {Proceedings - 2014 IEEE International Conference on Semantic Computing, ICSC 2014},
pages = {285–289},
publisher = {IEEE Computer Society},
abstract = {The paper proposes a system architecture for artificial creativity that enables a robot to perform portraits. The proposed cognitive architecture is inspired by the PSI model, and it requires that the motivation of the robot in the execution of its tasks is influenced by urges. Such parameters depend on both internal and external evaluation mechanisms. The system is a premise for the development of an artificial artist able to develop a personality and a behavior that depends on its experience of successes and failures (competence), and the availability of different painting techniques (certainty). The creative execution is driven by the motivation arising from the urges, and the perception of the work being executed or performed. The external evaluation is obtained by analyzing the opinions expressed in natural language from people watching the realized portrait. © 2014 IEEE.},
keywords = {Artificial intelligence, Chatbots, Cognitive Architectures, Computational Creativity, Creative Agents, Motivation, Natural Language Processing, PSI, Semantic Computing, Social Robots},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper proposes a system architecture for artificial creativity that enables a robot to perform portraits. The proposed cognitive architecture is inspired by the PSI model, and it requires that the motivation of the robot in the execution of its tasks is influenced by urges. Such parameters depend on both internal and external evaluation mechanisms. The system is a premise for the development of an artificial artist able to develop a personality and a behavior that depends on its experience of successes and failures (competence), and the availability of different painting techniques (certainty). The creative execution is driven by the motivation arising from the urges, and the perception of the work being executed or performed. The external evaluation is obtained by analyzing the opinions expressed in natural language from people watching the realized portrait. © 2014 IEEE.
2013
Augello, Agnese; Infantino, Ignazio; Pilato, Giovanni; Rizzo, Riccardo; Vella, Filippo
Introducing a Creative Process on a Cognitive Architecture Journal Article
In: Biologically Inspired Cognitive Architectures, vol. 6, pp. 131–139, 2013, ISSN: 2212683X.
Abstract | Links | BibTeX | Tags: Cognitive Architectures, Computational Creativity, Creative Process, Emotion Analysis, Motivation
@article{augelloIntroducingCreativeProcess2013,
title = {Introducing a Creative Process on a Cognitive Architecture},
author = { Agnese Augello and Ignazio Infantino and Giovanni Pilato and Riccardo Rizzo and Filippo Vella},
doi = {10.1016/j.bica.2013.05.011},
issn = {2212683X},
year = {2013},
date = {2013-01-01},
journal = {Biologically Inspired Cognitive Architectures},
volume = {6},
pages = {131--139},
abstract = {In this paper we present a system that implements a creative behavior on a cognitive architecture. It is aimed at creating digital art images from snapshots of a human subject, simulating a simple creative process. Such a process starts from a Training Phase that creates a set of image filter sequences. This phase is oriented to approximate some painting styles obtained from famous images and portraits of the past. The learned filter sequences are then used during the Production Phase. During this subsequent phase, the "artificial artist" interacts with the subject trying to "catch" the human emotions that drive the creation of the portrait. The artist processes feedbacks from the user according to the cognitive model Psi and its implementation of the motivations. These motivations influence further modifications of the applied filter sequences achieving an evolution of the artificial artist. textcopyright 2013 Elsevier B.V. All rights reserved.},
keywords = {Cognitive Architectures, Computational Creativity, Creative Process, Emotion Analysis, Motivation},
pubstate = {published},
tppubtype = {article}
}
In this paper we present a system that implements a creative behavior on a cognitive architecture. It is aimed at creating digital art images from snapshots of a human subject, simulating a simple creative process. Such a process starts from a Training Phase that creates a set of image filter sequences. This phase is oriented to approximate some painting styles obtained from famous images and portraits of the past. The learned filter sequences are then used during the Production Phase. During this subsequent phase, the "artificial artist" interacts with the subject trying to "catch" the human emotions that drive the creation of the portrait. The artist processes feedbacks from the user according to the cognitive model Psi and its implementation of the motivations. These motivations influence further modifications of the applied filter sequences achieving an evolution of the artificial artist. textcopyright 2013 Elsevier B.V. All rights reserved.
Augello, Agnese; Infantino, Ignazio; Pilato, Giovanni; Rizzo, Riccardo; Vella, Filippo
Introducing a creative process on a cognitive architecture Journal Article
In: Biologically Inspired Cognitive Architectures, vol. 6, pp. 131–139, 2013, ISSN: 2212683X.
Abstract | Links | BibTeX | Tags: Cognitive Architectures, Computational Creativity, Creative Process, Emotion Analysis, Motivation
@article{augello_introducing_2013,
title = {Introducing a creative process on a cognitive architecture},
author = {Agnese Augello and Ignazio Infantino and Giovanni Pilato and Riccardo Rizzo and Filippo Vella},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883260536&doi=10.1016%2fj.bica.2013.05.011&partnerID=40&md5=2df560e32408e4fe27f412efe0a12b19},
doi = {10.1016/j.bica.2013.05.011},
issn = {2212683X},
year = {2013},
date = {2013-01-01},
journal = {Biologically Inspired Cognitive Architectures},
volume = {6},
pages = {131–139},
abstract = {In this paper we present a system that implements a creative behavior on a cognitive architecture. It is aimed at creating digital art images from snapshots of a human subject, simulating a simple creative process. Such a process starts from a Training Phase that creates a set of image filter sequences. This phase is oriented to approximate some painting styles obtained from famous images and portraits of the past. The learned filter sequences are then used during the Production Phase. During this subsequent phase, the "artificial artist" interacts with the subject trying to "catch" the human emotions that drive the creation of the portrait. The artist processes feedbacks from the user according to the cognitive model Psi and its implementation of the motivations. These motivations influence further modifications of the applied filter sequences achieving an evolution of the artificial artist. © 2013 Elsevier B.V. All rights reserved.},
keywords = {Cognitive Architectures, Computational Creativity, Creative Process, Emotion Analysis, Motivation},
pubstate = {published},
tppubtype = {article}
}
In this paper we present a system that implements a creative behavior on a cognitive architecture. It is aimed at creating digital art images from snapshots of a human subject, simulating a simple creative process. Such a process starts from a Training Phase that creates a set of image filter sequences. This phase is oriented to approximate some painting styles obtained from famous images and portraits of the past. The learned filter sequences are then used during the Production Phase. During this subsequent phase, the "artificial artist" interacts with the subject trying to "catch" the human emotions that drive the creation of the portrait. The artist processes feedbacks from the user according to the cognitive model Psi and its implementation of the motivations. These motivations influence further modifications of the applied filter sequences achieving an evolution of the artificial artist. © 2013 Elsevier B.V. All rights reserved.