Abdelkader Gouaich

Weak Interaction and Strong Interaction in Agent Based Simulations

This paper addresses the problem of the engineering divergence phenomenon in ABS. This problem is related to the fact that a particular conceptual model may give different outputs according to its implementation. Through two experiments, the paper shows that the implementation of the agents’ interaction is one of the factors that are involved in this phenomenon. The underlying idea of this paper is that this problem can be greatly diminished if the analysis of the conceptual model incorporates some key concepts which are crucial for the implementation. To this end, this work proposes to identify two different classes of interaction: weak interactions and strong interactions.

Adaptation in serious games for upper-limb rehabilitation: an approach to improve training outcomes

In this paper, we propose a game adaptation technique that seeks to improve the training outcomes of stroke patients during a therapeutic session. This technique involves the generation of customized game levels, which difficulty is dynamically adjusted to the patients’ abilities and performance. Our goal was to evaluate the effect of this adaptation strategy on the training outcomes of post-stroke patients during a therapeutic session. We hypothesized that a dynamic difficulty adaptation strategy would have a more positive effect on the training outcomes of patients than two control strategies, incremental difficulty adaptation and random difficulty adaptation. To test these strategies, we developed three versions of PRehab, a serious game for upper-limb rehabilitation. Seven stroke patients and three therapists participated in the experiment, and played all three versions of the game on a graphics tablet. The results of the experiment show that our dynamic adaptation technique increases movement amplitude during a therapeutic session. This finding may serve as a basis to improve patient recovery.

Digital-pheromone based difficulty adaptation in post-stroke therapeutic games

In this paper, we propose a dynamic difficulty adaptation approach for serious games dedicated to upper-limb rehabilitation after stroke. The proposed approach aims to provide a personalized rehabilitation session in which the training intensity and challenges can be adapted to patients abilities and training needs. The objective is to increase the rehabilitation volume by getting the patient engaged in the therapy session. This approach has been implemented and tested through a point and click game. It has been also experimented on healthy people in order to explain how this approach will be integrated to post-stroke therapeutic games.

Dynamic Difficulty Adaptation in Serious Games for Motor Rehabilitation

In the last few years, a growing interest has been devoted to improve rehabilitation strategies by including serious games in the therapy process. Adaptive serious games seek to provide the patients with an individualized rehabilitation environment that meets their training needs. In this paper, a dynamic difficulty adaptation (DDA) technique is suggested. This technique focuses on the online adaptation of the game difficulty by taking into account patients’ abilities and motivation. The results of the experiment show that the adaptation technique increases the number of tasks, number of successful tasks as well as the movement amplitude during a game session. The technique positively effects the training outcomes of stroke patients, which can help them to recover their functions.

REST-A: An Agent Virtual Machine Based on REST Framework

This article presents a framework based on agent concepts and REST architectural style. Based on this framework, an agent virtual machine along with its operational semantics are introduced. The idea is to consider agents’ actions as manipulation of resources within environments using only a limited set of primitives. This makes both the agent abstract machine and its operational semantics easy to comprehend and the implementation straightforward. Finally, performances of our implementation are evaluated using a simple benchmark application.

Trajectory formation principles are the same after mild or moderate stroke

When we make rapid reaching movements, we have to trade speed for accuracy. To do so, the trajectory of our hand is the result of an optimal balance between feed-forward and feed-back control in the face of signal-dependant noise in the sensorimotor system. How far do these principles of trajectory formation still apply after a stroke, for persons with mild to moderate sensorimotor deficits who recovered some reaching ability? Here, we examine the accuracy of fast hand reaching movements with a focus on the information capacity of the sensorimotor system and its relation to trajectory formation in young adults, in persons who had a stroke and in age-matched control participants. We find that persons with stroke follow the same trajectory formation principles, albeit parameterized differently in the face of higher sensorimotor uncertainty. Higher directional errors after a stroke result in less feed-forward control, hence more feed-back loops responsible for segmented movements. As a consequence, movements are globally slower to reach the imposed accuracy, and the information throughput of the sensorimotor system is lower after a stroke. The fact that the most abstract principles of motor control remain after a stroke suggests that clinicians can capitalize on existing theories of motor control and learning to derive principled rehabilitation strategies.

Automatic annotation using citation links and co-citation measure: application to the water information system

This paper describes an approach to automatically annotate documents for the Euro-Mediterranean Water Information System This approach uses the citation links and co-citation measure in order to refine annotations extracted from an indexation method An experiment of this approach with the CiteSeer database is presented and discussed.

Network Aware Traffic Adaptation for Cloud Games

Current cloud gaming systems have very strong requirements in terms of network resources. For pervasive gaming in various environments like at home, hotels, internet cafes, or area with limited or unstable network access, it is beneficial to avoid the necessity of having a costly steady fast speed internet connection to be able to run these cloud games. We present a network aware adaptation technique based on the level of detail (LoD) approach in 3D graphics. It maintains a bidirectional multi-level quality of service for game entities at runtime, lessening the games communication cost when it notices a decrease in network resources and maintains an optimal communication frequency otherwise. It therefore reduces the impact of poor and unstable network parameters (delay, packet loss, jitter) on game interactivity while improving users quality of experience (QoE). The evaluation of our approach through a pilot experiment shows that the proposed technique provides a significant QoE enhancement.

Agora UCS Ubiquitous Collaborative Space

Agora UCS is a new architecture designed for distributed learning as a side effect of communication and collaboration. This architecture aims to achieve (i) ubiquity (time and space independent access by community members); (ii) immanence (full internal control of the destiny of the community) and (iii) multi-modal communication (reinforcing the interactions between the members of the community). The theoretical model underlying Agora UCS is inspired by an integration of agents and Grid concepts (AGIL). Agora UCS has been experimented by a dozen of communities, which represent alltogether about seventy members. We achieved quite promising results in terms of motivation and collective performances.

A players clustering method to enhance the players' experience in multi-player games

Online multi player games are a kind of video game where players have to interact together in a same game environment through an Internet connection. In these games, the players are grouped in different sessions where they can only interact with the member of the session. In order to maximize the players experience, game designers have to solve different issues. The first one is to maximize the number of players in the different game sessions. As these game are designed to provide the better game experience when the maximum number of players are in the session. It is important to avoid session with few players. The second one is to create session where the players have the same skill level. A too large difference between the level skills of the players can create frustration. In this short paper we focus on players skill and present an approach in development to automatically detect communities of players in order to create game session. Our approach is based on game play component, user profile and player interaction with the different game play component. We describe the experiment scheme that has been designed in order to evaluate the impact of the proposition on player satisfaction.