Context-based decision-making for virtual soccer players.

International audienceThis article introduces a decision-making model for virtual agents evolving in dynamic and collaborative situations. Agents and humans have to collaborate in a virtual environment. In order to enhance the collaboration, the agent decision-making model is based on notions close to human ones. Those notions are context and case based reasoning. After an introduction of dynamic and collaborative situations, we present the notion of context and we give a definition adapted to our framework. The next part describes the decision making process. This one relies on the case identification thanks to a graph search algorithm. The last part of this document illustrates our purpose with an example taken from our application

Understanding dynamic situations through context explanation.

International audienceThis article presents advantages of using context to set up a pedagogical assistance for recognition of collectives situations in Virtual Environment for Training (VET). We are focusing on generation of explanations to the learner. Two assistances types have been envisaged thanks to context using, the first one consists in guiding the learner before action and the second can be used during action. Those assistances have been set up thanks to contextual graph and consists of animations in the virtual environment

Real-time retrieval for case-based reasoning in interactive multiagent-based simulations

The aim of this paper is to present the principles and results about case-based reasoning adapted to real- time interactive simulations, more precisely concerning retrieval mechanisms. The article begins by introducing the constraints involved in interactive multiagent-based simulations. The second section pre- sents a framework stemming from case-based reasoning by autonomous agents. Each agent uses a case base of local situations and, from this base, it can choose an action in order to interact with other auton- omous agents or users' avatars. We illustrate this framework with an example dedicated to the study of dynamic situations in football. We then go on to address the difficulties of conducting such simulations in real-time and propose a model for case and for case base. Using generic agents and adequate case base structure associated with a dedicated recall algorithm, we improve retrieval performance under time pressure compared to classic CBR techniques. We present some results relating to the performance of this solution. The article concludes by outlining future development of our project

Context's modeling for participative problem solving

International audienceThis paper reviews the interest of using context for participative simulation in virtual environment for training. Context is an interesting concept for at least two points: Virtual agents and humans have to collaborate ,so they must communicate and understand each other. This is the reason why we use a simplified analogy with human's decision-making. Our aim is to simulate some cognitive mechanisms in order to have credible agent's decision-making. We keep the notion of context. Agents reason with the situation's context, which is divided in social, environmental, historical and personal contexts. Another interesting aspect is the explanation needed when the learner makes a mistake. We argue, in this article, that context is a good concept to give better explanations. At last we show an example of an agent decision-making

Interactive co-construction to study dynamical collaborative situations.

International audienceThe purpose of this paper is to present the principle of our framework CoPeFoot dedicated to the study of dynamic and collaborative situations. This research work aims to instate learning by the co-construction of such situations. The article starts by recalling constraints induced by such situations. Next, it introduces interactive co-construction assumption and their implementation in CoPeFoot. In fact, this implementation is based on two steps in CoPeFoot: firstly, machine learning for behavior modeling, using imitation of real users and secondly, refining this behavior by using interaction between the user and the simulation, enhanced by additional information called augmented virtuality. In order to do that, CoPeFoot lies on context base reasoning which is presented. The article ends by a first evaluation of this work

Context: An Information Medium for Dynamic and Collaborative Situations

International audienceWe introduce, in this article, a way for building a Virtual Environment for Training to manage dynamic and collaborative situations in team sport. In these situations, relevant information can not be totally known in advance. Autonomous agents can only reason with few pieces of information and explanations on the situation are numerous and not easily predictable. We introduce, in this paper, the usefulness of the notion of context, in a VET, to set up agent decision-making and to generate explanations in order to help the learner. The main purpose of this article is that the context is a medium facilitating information reuse

Virtual Reality for Research and Training in Sport: an Illustration with CoPeFoot

International audienceNew possibilities for research and training in sport could be offered thanks to virtual reality simulations. The literature is examined, analysing the advantages and properties of current simulators. This paper aims to present an original experiment in virtual reality simulation design based on autonomy, interaction and evolving concepts. Our main suggestion is that believability of simulation for the user needs both regularity and surprises (in terms of virtual agents' behaviour). A naturalistic approach was used to study experts' decision-making processes in soccer settings. The decision-making model represented a guideline for choosing and implementing computational models. The advantages of virtual reality simulation are discussed in relation to training and research in sports science