Actas y comunicaciones de congresos

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Cost-effectiveness analysis with decision analysis networks
(Asociación Española para la Inteligencia Artificial, 2021-08-24) Díez Vegas, Francisco Javier; Luque Gallego, Manuel; Arias Calleja, Manuel; Pérez Martín, Jorge; Agencia Estatal de Investigación (España)
Decision analysis networks (DANs) are a new type of probabilistic graphical model. Like influence diagrams (IDs), they are much more compact and easier to build than decision trees and can represent conditional independencies, but they can also represent problems involving partial orderings of the decisions (order asymmetry) and other types of asymmetry. Given that DANs can solve symmetric problems as easily and as efficiently as IDs, and are more appropriate for asymmetric problems—which include virtually all real-world problems—DANs might replace IDs as the standard type of probabilistic graphical model for decision analysis. In particular, they can be use to perform cost-effectiveness analyses (CEAs), which are used increasingly in medicine to determine whether the health benefit of an intervention is worth the economic cost.
Las damas nobles en la ciudad en la Edad Moderna: espacios y relatos de vidaLas damas nobles en la ciudad en la Edad Moderna: espacios y relatos de vida
(Ediciones Doce Calles/ Universidad Complutense, 2025-01-01) Antorán Pilar, Guiomar; Agencia Estatal de Investigación (España)
Harmonizing Ethical Principles: Feedback Generation Approaches in Modeling Human Factors for Assisted Psychomotor Systems
(Association for Computing Machinery, Inc, 2024-06-28) Portaz Collado, Miguel Ángel; Manjarrés Riesco, Ángeles; Santos, Olga C.; Agencia Estatal de Investigación (España)
As the demand for personalized and adaptive learning experiences increase, there is a urgent need for providing effective feedback mechanisms within critical systems, such as in psychomotor learning systems. This proposal introduces an approach for the integration of retrieval-augmented generation tools to provide comprehensive and insightful feedback to users. By combining the strengths of retrieval-based techniques and generative models, these tools offer the potential to enhance learning outcomes by delivering tailored feedback that is both informative and engaging. The proposal also emphasises the importance of incorporating explainability and transparency concepts. Following the hybrid intelligence paradigm it is possible to ensure that the feedback provided by these tools is not only accurate but also understandable to humans. This approach fosters trust and promotes a deeper understanding of the psychomotor learning process, empowering users and facilitators to make informed decisions about the psychomotor learning path. The hybrid intelligence paradigm, which combines the strengths of both human and artificial intelligence, plays a crucial role in the deployment of these solutions. By taking advantage of the cognitive capabilities of human experts alongside the computational power of artificial intelligence algorithms, it is possible to offer personalised feedback that takes into account both technical accuracy and pedagogical effectiveness. Through these collaborative efforts it is also possible to create learning environments that are inclusive, adaptable, and beneficial to lifelong learning. In conclusion, this proposal introduces retrieval-augmented generation tools for providing feedback in psychomotor learning systems, which represents a significant step towards in its personalization, and whose ethical implications align with the new regulations on the implementation of intelligent technologies in critical systems.
Le jardin peint d’une domus suburbaine de Tarraco (Tarragone, Espagne)
(Ausonius, 2025-11-20) Guiral Pelegrín, Carmen; Íñiguez Berrozpe, Lara; Lashera González, Ada; Agencia Estatal de Investigación (España)
Nous présentons quatre panneaux peints provenant de la cour à portique d’une des domus suburbaines de Tarraco et actuellement conservés au Musée archéologique national de Tarragone. L’analyse de ces panneaux a permis de déduire que le parapet qui faisait partie du portique de cette pièce était décoré de scènes sur fond blanc encadrées de bandes rouges. Deux panneaux correspondants à la face interne de cette structure figurent un paysage sur le côté nord et un paon sur le côté sud ; un troisième panneau correspondant à la face externe, également au nord, représente une scène de chasse. La quatrième plaque retrouvée, avec un hortus pictus sur fond blanc, faisait partie d’une peinture de jardin qui s’étendait vraisemblablement sur tout le mur ouest adjacent au triclinium. Toute la décoration a été réalisée en même temps et par le même atelier, au iie s. p.C., après un éventuel remaniement partiel de la pièce, compte tenu de la différence d’exécution et de l’orientation du parapet sud.
Simulating Misinformation Diffusion on Social Media Through CoNVaI: A Textual- and Agent-Based Diffusion Model
(International Joint Conferences on Artificial Intelligence, 2025-09) Rodríguez García, Raquel; Centeno Sánchez, Roberto; Rodrigo Yuste, Álvaro; Agencia Estatal de Investigación (España)
Misinformation has experienced increased online diffusion, leveraging strategies, such as emotional manipulation, to influence users' opinions. Efforts are underway to develop tools to mitigate its effects, such as misinformation propagation models used to simulate the diffusion of information. There are different approaches within these models, although, they show a significant limitation by disregarding the content of the information shared, crucial to the diffusion. We consider it the central aspect of modeling information dissemination. To this end, we focus on Agent-Based Modeling due to its suitability to simulate the complex interactions and heterogeneous behaviors observed on social media. We base our approach on a state-of-the-art Agent-Based Model that we modify and extend to account for the texts of the messages shared, focusing on two aspects that influence agents' decisions: i) the novelty of the content and; ii) its diffusion and behavior over time. To determine whether this content proves informative, we conduct an empirical evaluation using social media data from Twitter. Based on our experimental results, we observe that our textual-based approach reflects information diffusion more realistically than the state of the art, reducing the error regarding real diffusion.
Towards Human-Centric Psychomotor Recommender Systems
(Association for Computing Machinery, Inc, 2023-06-16) Portaz Collado, Miguel Ángel; Manjarrés Riesco, Ángeles; Santos, Olga C.; Agencia Estatal de Investigación (España)
Recommender Systems have been developed for years to guide the interaction of the users with systems in very diverse domains where information overload exists aimed to help humans in decision making. In order to better support the humans, the more the system knows about the user, the more useful recommendations the user can receive. In this sense, there is a need to explore which are the intrinsic human aspects that should be taken into account in each case when building the user models that provide the personalization. Moreover, there is a need to define and apply methodologies, guidelines and frameworks to develop this kind of systems in order to tackle the challenges of current artificial intelligence applications including issues such as ethics, transparency, explainability and sustainability. For our research, we have chosen the psychomotor domain. To provide some insights into this problem, in this paper we present the research directions we are exploring to apply a human-centric approach when developing the iBAID (intelligent Basket AID) psychomotor system, which aims to recommend the physical activities and movements to perform when training in basketball, either to improve the technique, to recover from an injury or even to keep active when getting older.

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