Human-aware robotic navigation remains an open challenge, with no universal solution yet available. Recent advances in the field have identified key metrics and scenarios that such navigation systems should address. In this paper, we present a novel social robotic navigation solution based on a heuristic approach that yields good performance in various environments (open areas or corridors) and different conditions (absence of human to crowded). Simulations first show the lack of generalization of existing methods and that our approach compete with baselines in crowded scenarios and outperforms them across daily scenarios (corridors), using a well-established set of metrics in the field. Preliminary real-world experiment further demonstrate the feasibility of deploying this approach in dynamic environments involving humans.

Higher Education is constantly pushing to include soft skills in their curricula. An alternative could be to personalise their curricula so that students could better develop their soft skills. However, there are not many studies that investigate how to personalise the students' curricula based on their soft skills, especially if we consider multiple soft skills that need development. The aim of the article is to propose a recommender system framework based on soft skills in order to bridge the soft skills gap between the expected proficiency by employers and the actual proficiency of graduates. The approach is illustrated using real data from three cohorts of students that graduated in the years 2021, 2022 and 2023 at a French Higher Education Institution. We use a psychometric modelling approach to predict the soft skills proficiency of students within a genetic algorithm framework. We define three fitness functions and two aggregation methods, with which we can quantify the relevance of a set of courses across 10 different soft skills (e.g., Problem Solving, Leadership). The results show the recommendations to have, on average, a higher fitness than the actual courses taken by the students during the program. Moreover, there is significant evidence that the recommendations would allow the students to satisfy more of the soft skill targets compared to the courses the students actually took.

In recent years, the number of robotic applications in public spaces has been growing. Decades of research have given rise to various methods of human-aware robotic navigation. There are a lot of different navigation solutions to guide a robot in presence of humans. Despite multiple surveys comparing existing navigation solutions, few of them take social criteria into account. In this sense, it is difficult to evaluate existing methods and select the one that performs better in a given context. In this article, we first provide a thorough classification of state-of-the-art solutions regarding human-aware robotic navigation solutions. Then, we select a set of measurable criteria to evaluate both the efficiency and the social-compliance of navigation solutions. Using these criteria, we finally compare representative off-the-shelf navigation solutions using the SEAN Simulator to identify the most suitable for human-aware navigation.

Over the last decade, Higher Education has focused more of its attention toward soft skills compared to traditional technical skills. Nevertheless, there are not many studies concerning the relation between the courses followed within an academic program and the development of soft skills. This work presents a practical approach to model the effects of courses on soft skills proficiency. Multiple Membership Ordinal Logistic Regression models are trained with real data from students of the 2021, 2022, and 2023 cohorts from the general engineering program in a French Higher Education institution. The results show that attending a postgraduate course in average increases the odds of being more proficient in terms of soft skills. Nonetheless, there is considerable variability in the individual effect of courses, which suggest there can be huge differences between courses. Moreover, the data also suggest great dispersion in the students' initial soft skill proficiency.

In this work, we propose a distributed Memetic Algorithm for the traveling salesman problem focusing on small and medium-sized instances. The algorithm employs a new crossover operator that favors the fitter of the two parents and develops varying progeny from the same parents to evade premature convergence. In the implementation, we use the High-Level Architecture (HLA) to distribute laborious tasks and lower the lead time of the heuristic. Results show that our proposed approach significantly outperforms other algorithms when tested on instances from the TSPLIB benchmark.

In order to monitor and assess the spread of the Omicron variant of COVID-19, we propose a Distributed Digital Twin that virtually mirrors a hemodialysis unit in a hospital in Toronto, Canada. Since the solution involves heterogeneous components, we rely on the IEEE HLA distributed simulation standard. Based on the standard, we use an agent-based/discrete event simulator together with a virtual reality environment in order to provide to the medical staff an immersive experience that incorporates a platform showing predictive analytics during a simulation run. This can help professionals monitor the number of exposed, symptomatic, asymptomatic, recovered, and deceased agents. Agents are modeled using a redesigned version of the susceptible-exposed-infected-recovered (SEIR) model. A contact matrix is generated to help identify those agents that increase the risk of the virus transmission within the unit.

Introduced in 2013, the A.L.P.E.S. approach (AgiLe aPproaches in higher Education Studies) aims to apply agile practices to teaching. Agile approaches are project management practices for IT development. More pragmatic than traditional methods, they allow to be closer to the applicant and to involve him/her as much as possible. They offer a great reactivity and a good adaptation to best meet the needs. They are used today in a large part of IT companies. Largely inspired by agile approaches, the A.L.P.E.S. approach allows the teaching of project management in a transverse way to a main course. It makes teaching more flexible and more adapted to the students. In this article, we describe the approach. We describe the tools, the process of creating a course, and the process of running a course.

Cet article presente les travaux qui serviront de base a la realisation d'un modele d'habitat intelligent adaptatif multi-residents centre utilisateur. Nous y presentons en premier lieu le contexte qui nous amene a proposer ce projet, puis nous dressons un etat de l'art des travaux relies a notre projet. Nous concluons enfin sur le positionnement de notre demarche par rapport a l'existant ainsi que sur une discussion sur les perspectives en cours et envisagees.

La pedagogie par projet a su montrer son efficacite et l'on constate un accroissement de sa popularite dans l'enseignement superieur. Cette pratique met l'accent sur les competences interdisciplinaires relatives a la gestion de projet que les etudiants sont amenes a mobiliser durant tout leur cursus. Nous nous interessons plus particulierement a la gestion de projet en informatique centree humain, qui fait intervenir l'humain dans les processus de conception, d'utilisation et d'evaluation des projets. Dans cet article, nous abordons les questions de l'integration et de l'evaluation de ces competences interdisciplinaires chez les etudiants. Premierement, nous traitons la question de la tracabilite de l'apprentissage de ces competences dans le contexte de l'informatique centree humain en adoptant une approche par competences. Nous argumentons les avantages et les desavantages des approches existantes dans le contexte des methodes Agiles dans la pedagogies par projet centree humain. Deuxiemement, nous presentons des outils capables d'accompagner ce type de projet, et l'effet qu'ils ont sur l'enseignement, le cadre ecologique des enseignants et la motivation des etudiants. Des entretiens semi-directifs ont ete realises avec cinq enseignants concernant ces deux questions. Une des conclusions a ces entretiens est la necessite de pouvoir tracer et analyser la progression des etudiants durant ces cours afin de pouvoir les aider de maniere adequat et de s'assurer de l'acquisition des competences a la fois disciplinaires dont les enseignants sont experts, et celles interdisciplinaires de gestion de projet. Dans ce but nous proposons le projet APACHES, co-construit avec ces differents acteurs.

This work is a part of a project concerned with providing immersive and realistic experiences in video and serious games. Among other questions, the project relates to finding the best approach to represent and analyze game logs (traces) in order to improve the player experience through, for example, adaptive game flow. Understanding the player’s profile is one key point towards adaptive, personalized and immersive experiences. To this end, this paper aims to present a non-intrusive approach to calculate the player’s profile by analyzing his/her game traces (indirect profiling). This calculation is based on in-game information like the current situation and the player interactions with non-player characters. The representation of the player’s profile is based on a social-psychological model called the dispositional approach using 4 dimensions: time, control, motivation and relations. Pilot experiments were run with registered game traces of 15 participants playing a serious game on change management in professional environments. Calculated players’ profiles from traces analysis are then compared with the profiles issued from a dispositional profiling questionnaire and a post-game interview with a social expert. This first experiment shows that applying a trace-based approach for player profiling can be efficient. It also highlights that when game instructions and objectives are specific and precise, they can cause a deviation of the player behavior from his/her real-life behavior and personality.

Les jeux serieux, ou serious games, deviennent des dispositifs de formation en plein essor. Le realisme des situations et la coherence des personnages rencontres au cours des scenarios proposes sont cruciaux pour offrir a l'utilisateur une experience immersive, favorisant l'apprentissage. Cet article presente la conception et l'evaluation d'un serious game centre sur les interactions sociales. Si l'apport de technologies d'intelligence artificielle portant sur les aspects sociaux et emotionnels de l'interaction semble ameliorer l'experience de jeu, l'importance de mettre en place un dispositif d'accompagnement humain autour du serious game lui-meme est preponderante. Par ailleurs, les methodologies permettant d'evaluer l'apport de personnages animes emotionnels a l'interaction doivent etre discutees.

Human-centered project-based teaching methods have proved their efficiency and popularity in the last decade. Such practice emphasizes the existence of interdisciplinary skills that students manipulate and incrementally learn to master throughout their higher education curriculum. This paper addresses some questions around the integration and evaluation of interdisciplinary skills. The first question focuses on the establishment of a skill-based approach to keep track of the students' competencies over human-centered computing skills all along their curriculum. To this end, we discuss the advantages and disadvantages of existing approaches in the context of agile practices and interdisciplinary skills in human-centered project-based teaching methods. The second question deals with the tools that can accompany such approach and how they can affect the teaching courses, the university instructors' habits and the motivation of the students. A semi-structured interviews were conducted with five instructors regarding these two questions. One main conclusion is the need to keep track of the students progress during the courses to help an efficient follow up. For this end, we propose to co-design a framework named APACHES.

In this work, we set the bases of the integration of ambient intelligence (AmI) with mobile robot teams (MRT), aiming to enhance ambient assisted living services addressing a variety of tasks. We argue that people with reduced mobility can benefit from a synergy between AmI and MRT in various aspects. Towards this direction, we identify principal functionalities such an integrated system should provide in connection to relevant previous works and the way by which synergy could be accomplished, from low-level behavioural to higher-level task planning of a multi-layered system architecture.

An integrated network of mobile robots, personal smart devices, and smart spaces called “Robots-Assisted Ambient Intelligence” (RAmI) can provide for a more effective user assistance than if the former resources are used individually. Additionally, with the application of distributed network optimization, not only can we improve the assistance of an individual user, but we can also minimize conflict or congestion created when multiple users in large installations use the limited resources of RAmI that are spatially and temporally constrained. The emphasis of RAmI is on the efficiency and effectiveness of multiple and simultaneous user assistance and on the influence of an individual’s actions on the desired system’s performance. In this paper, we model RAmI as a multi-agent system with AmI, user, and robot agents. Moreover, we propose a modular three-layer architecture for each robot agent and discuss its application and communication requirements to facilitate efficient usage of limited RAmI resources. Our approach is showcased by means of a case study where we focus on meal and medicine delivery to patients in large hospitals.

Several machine learning approaches are used to train systems and agents while exploiting usersu0027 feedback over the given service. For example, different semi-supervised approaches employ this kind of information in the learning process to guide the agent to a more adaptive and possibly person-alized behavior. Whether for recommendation systems , companion robots or smart home assistance, the trained agent must face the challenges of adapting to different users (with different profiles, preferences , etc.), coping with dynamic environments (dynamic preferences, etc.) and scaling up with a minimal number of training examples. We are interested in this paper in one-step decision making for adaptive and user-dependent services using usersu0027 feedback. We focus on the quality of such services while dealing with ambiguities (noise) in the received feedback. We describe our problem and we concentrate on presenting a state of the art of possible methods that can be applied. We detail two algorithms that are based on existing approaches. We present comparative results by showing scaling and convergence analysis with clean and noisy simulated data.