Video games and Intellectual Disabilities: a literature review.

Los videojuegos son omnipresentes en la sociedad y esta tecnología ha trascendido su lado lúdico inicial para convertirse también en una herramienta educativa y de entrenamiento cognitivo. En este sentido, diferentes estudios han demostrado que los jugadores expertos obtener ventajas en diversos procesos cognitivos respecto a no-jugadores y jugar con juegos de video puede resultar en especial los beneficios que en algunos casos podría generalizarse a otras tareas. En consecuencia, los juegos de video podría ser utilizado como una herramienta de formación para mejorar las capacidades cognitivas en poblaciones atípicas, como las relativas a las personas con discapacidad intelectual (DI). Sin embargo, la literatura sobre los videojuegos en personas con ID es escasa. En este trabajo se ejecutó una revisión narrativa de los estudios sobre el uso de los videojuegos en relación a las personas con ID.Video games are ubiquitous in the society and this technology has transcended its initial playful side to become also an educational and cognitive training tool. In this sense, different studies have shown that expert game players gain advantages in various cognitive processes respect to non-players and that playing with video games can result in particular profits that in some cases could be generalized to other tasks. Accordingly, video games could be used as a training tool in order to improve cognitive abilities in atypical populations, such as relating to individuals with intellectual disabilities (ID). However, literature concerning video games in people with ID is sparse. In this paper we executed a narrative review of the studies about the use of video games in relation to people with ID.• Fundación Valhondo Calaff (Cáceres), para Marta Rodríguez Jiménez • Università di Padova. Beca CPDA 127939, para Silvia LanfranchipeerReviewe

Object-Oriented Dynamics Learning through Multi-Level Abstraction

Object-based approaches for learning action-conditioned dynamics has demonstrated promise for generalization and interpretability. However, existing approaches suffer from structural limitations and optimization difficulties for common environments with multiple dynamic objects. In this paper, we present a novel self-supervised learning framework, called Multi-level Abstraction Object-oriented Predictor (MAOP), which employs a three-level learning architecture that enables efficient object-based dynamics learning from raw visual observations. We also design a spatial-temporal relational reasoning mechanism for MAOP to support instance-level dynamics learning and handle partial observability. Our results show that MAOP significantly outperforms previous methods in terms of sample efficiency and generalization over novel environments for learning environment models. We also demonstrate that learned dynamics models enable efficient planning in unseen environments, comparable to true environment models. In addition, MAOP learns semantically and visually interpretable disentangled representations.Comment: Accepted to the Thirthy-Fourth AAAI Conference On Artificial Intelligence (AAAI), 202

Grounding semantics in robots for Visual Question Answering

In this thesis I describe an operational implementation of an object detection and description system that incorporates in an end-to-end Visual Question Answering system and evaluated it on two visual question answering datasets for compositional language and elementary visual reasoning

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Training verbal working memory in children with mild intellectual disabilities: effects on problem-solving

This multiple case study explores the effects of a cognitive training program in children with mild to borderline intellectual disability. Experimental training effects were evaluated comparing pre-post-test changes after (a) a baseline phase versus a training phase in the same participant, (b) an experimental training versus either a no intervention phase or a control training in two pairs of children matched for cognitive profile. Key elements of the training program included (1) exercises and card games targeting inhibition, switching, and verbal working memory, (2) guided practice emphasizing concrete strategies to engage in exercises, and (3) a variable amount of adult support. The results show that both verbal working memory analyzed with the listening span test and problem-solving tested with the Raven’s matrices were significantly enhanced after the experimental trainin

Expertise in chess

This chapter provides an overview of research into chess expertise. After an historical background and a brief description of the game and the rating system, it discusses the information processes enabling players to choose good moves, and in particular the trade-offs between knowledge and search. Other topics include blindfold chess, talent, and the role of deliberate practice and tournament experience