Search results for "GAM"
showing 10 items of 5334 documents
Teaching clinical reasoning and decision-making skills to nursing students: Design, development, and usability evaluation of a serious game
2016
Background\ud \ud Serious games (SGs) are a type of simulation technology that may provide nursing students with the opportunity to practice their clinical reasoning and decision-making skills in a safe and authentic environment. Despite the growing number of SGs developed for healthcare professionals, few SGs are video based or address the domain of home health care.\ud \ud Aims\ud \ud This paper aims to describe the design, development, and usability evaluation of a video based SG for teaching clinical reasoning and decision-making skills to nursing students who care for patients with chronic obstructive pulmonary disease (COPD) in home healthcare settings.\ud \ud Methods\ud \ud A prototy…
Process-and context-sensitive research on academic knowledge practices
2007
The Contextual Activity Sampling System (CASS) methodology and CASS-Query tools have been developed for the investigation of learning and working practices. The CASS-methods and tools provide contextualized data that allow the analyzing and modeling of within-person changes across time. This paper describes a pilot study with 3G mobiles used by eight engineering students. Students answered questionnaires concerning their ongoing study projects, academic emotions, and collaboration, with a mobile phone five times a day for a period of two weeks (70 queries per person). Variation in their emotions were examined by time-series analysis. Students were also interviewed before and after the CASS-…
Developing a Serious Game for Nurse Education.
2018
Future nursing education is challenged to develop innovative and effective programs that align with current changes in health care and to educate nurses with a high level of clinical reasoning skills, evidence-based knowledge, and professional autonomy. Serious games (SGs) are computer-based simulations that combine knowledge and skills development with video game–playing aspects to enable active, experiential, situated, and problem-based learning. In a PhD project, a video-based SG was developed to teach nursing students nursing care for patients with chronic obstructive pulmonary disease in home health care and hospital settings. The current article summarizes the process of the SG devel…
Harsanyi Power Solutions for Cooperative Games on Voting Structures
2019
International audience; This paper deals with Harsanyi power solutions for cooperative games in which partial cooperation is based on specific union stable systems given by the winning coalitions derived from a voting game. This framework allows for analyzing new and real situations in which there exists a feedback between the economic influence of each coalition of agents and its political power. We provide an axiomatic characterization of the Harsanyi power solutions on the subclass of union stable systems arisen from the winning coalitions from a voting game when the influence is determined by a power index. In particular, we establish comparable axiomatizations, in this context, when co…
Density Flow in Dynamical Networks via Mean-Field Games
2016
Current distributed routing control algorithms for dynamic networks model networks using the time evolution of density at network edges, while the routing control algorithm ensures edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We rearrange the density model to recast the problem within the framework of mean-field games. In doing that, we illustrate an extended state-space solution approach and we study the stochastic case where the density evolution is driven by a Brownian motion. Further, we investigate the case where the density evolution is perturbed by a bounded adversarial disturbance. For both the stochastic a…
Learning of Cooperative Behaviour in Robot Populations
2016
This paper addresses convergence and equilibrium properties of game theoretic learning algorithms in robot populations using simple and broadly applicable reward/cost models of cooperation between robotic agents. New models for robot cooperation are proposed by combining regret based learning methods and network evolution models. Results of mean-field game theory are employed in order to show the asymptotic second moment boundedness in the variation of cooperative behaviour. The behaviour of the proposed models are tested in simulation results, which are based on sample networks and a single lane traffic flow case study.
Adaptation, coordination, and local interactions via distributed approachability
2017
This paper investigates the relation between cooperation, competition, and local interactions in large distributed multi-agent\ud systems. The main contribution is the game-theoretic problem formulation and solution approach based on the new framework\ud of distributed approachability, and the study of the convergence properties of the resulting game model. Approachability\ud theory is the theory of two-player repeated games with vector payoffs, and distributed approachability is here presented for\ud the first time as an extension to the case where we have a team of agents cooperating against a team of adversaries under local\ud information and interaction structure. The game model turns i…
Bio-inspired evolutionary dynamics on complex networks under uncertain cross-inhibitory signals
2019
Given a large population of agents, each agent has three possiblechoices between option 1 or 2 or no option. The two options are equally favorable and the population has to reach consensus on one of the two options quickly and in a distributed way. The more popular an option is, the more likely it is to be chosen by uncommitted agents. Agents committed to one option can be attracted by those committed to the other option through a cross-inhibitory signal. This model originates in the context of honeybee swarms, and we generalize it to duopolistic competition and opinion dynamics. The contributions of this work include (i) the formulation of a model to explain the behavioral traits of the ho…
Opinion Dynamics and Stubbornness via Multi-Population Mean-Field Games
2016
This paper studies opinion dynamics for a set of heterogeneous populations of individuals pursuing two conflicting goals: to seek consensus and to be coherent with their initial opinions. The multi-population game under investigation is characterized by (i) rational agents who behave strategically, (ii) heterogeneous populations, and (iii) opinions evolving in response to local interactions. The main contribution of this paper is to encompass all of these aspects under the unified framework of mean-field game theory. We show that, assuming initial Gaussian density functions and affine control policies, the Fokker---Planck---Kolmogorov equation preserves Gaussianity over time. This fact is t…
Game Theoretic Decentralized Feedback Controls in Markov Jump Processes
2017
This paper studies a decentralized routing problem over a network, using the paradigm of mean-field games with large number of players. Building on a state-space extension technique, we turn the problem into an optimal control one for each single player. The main contribution is an explicit expression of the optimal decentralized control which guarantees the convergence both to local and to global equilibrium points. Furthermore, we study the stability of the system also in the presence of a delay which we model using an hysteresis operator. As a result of the hysteresis, we prove existence of multiple equilibrium points and analyze convergence conditions. The stability of the system is ill…