Combining computer game-based behavioural experiments with high-density EEG and infrared gaze tracking

Rigorous, quantitative examination of therapeutic techniques anecdotally reported to have been successful in people with autism who lack communicative speech will help guide basic science toward a more complete characterisation of the cognitive profile in this underserved subpopulation, and show the extent to which theories and results developed with the high-functioning subpopulation may apply. This study examines a novel therapy, the "Rapid Prompting Method" (RPM). RPM is a parent-developed communicative and educational therapy for persons with autism who do not speak or who have difficulty using speech communicatively.The technique aims to develop a means of interactive learning by pointing amongst multiple-choice options presented at different locations in space, with the aid of sensory "prompts" which evoke a response without cueing any specific response option. The prompts are meant to draw and to maintain attention to the communicative task–making the communicative and educational content coincident with the most physically salient, attention-capturing stimulus – and to extinguish the sensory–motor preoccupations with which the prompts compete.ideo-recorded RPM sessions with nine autistic children ages 8–14years who lacked functional communicative speech were coded for behaviours of interest

Self-tuning experience weighted attraction learning in games

Self-tuning experience weighted attraction (EWA) is a one-parameter theory of learning in games. It addresses a criticism that an earlier model (EWA) has too many parameters, by fixing some parameters at plausible values and replacing others with functions of experience so that they no longer need to be estimated. Consequently, it is econometrically simpler than the popular weighted fictitious play and reinforcement learning models. The functions of experience which replace free parameters “self-tune” over time, adjusting in a way that selects a sensible learning rule to capture subjects’ choice dynamics. For instance, the self-tuning EWA model can turn from a weighted fictitious play into an averaging reinforcement learning as subjects equilibrate and learn to ignore inferior foregone payoffs. The theory was tested on seven different games, and compared to the earlier parametric EWA model and a one-parameter stochastic equilibrium theory (QRE). Self-tuning EWA does as well as EWA in predicting behavior in new games, even though it has fewer parameters, and fits reliably better than the QRE equilibrium benchmark

Variable time scales, agent-based models, and role-playing games: The PIEPLUE river basin management game

This article presents a specific association of a role-playing game (RPG) and an agent-based model (ABM) aimed at dealing with a large range of time scales. Applications to the field of natural resource management lead one to consider the short time scale of resource use in practice at the same time as the longer ones related to resource dynamics or actors' investments. In their daily practice, stakeholders are translating their long-term strategies, a translation that is contextualized and combined with some cooccurring events. Long-term thinking is required for sustainable use of natural resources, but it should take into account its necessary adaptation on a short time scale. This raises the necessity for tools able to tackle jointly these various time scales. The similarity of architecture between computerized ABMs and RPGs makes them easy to associate in a hybrid tool, targeted at meeting this requirement. The proposition of this article is to allocate the representation of short time scales to computerized ABMs and the long ones to RPGs, while keeping the same static structural conceptual model, shared as a common root by both. This synergy is illustrated with PIEPLUE, an interactive setting tackling water-sharing issues.GESTION DE L'EAU;BASSIN VERSANT;RESSOURCE NATURELLE;MODELE;JEU DE ROLE;SYSTEME MULTIAGENTS;AGENT-BASED MODEL;CASE STUDY OF WATER SHARING;CONCEPTUAL MODEL;HYBRID TOOL;INVESTMENTS;LONG-TERM ISSUES;NATURAL RESOURCE MANAGEMENT;PIEPLUE;PARTICIPATORY MODELING;RESOURCE DYNAMICS;RESOURCE USE;ROLE-PLAYING GAME;STAKEHOLDERS;SUSTAINABLE USE OF NATURAL RESOURCES;TIME-SCALE DIVERSITY;VARIABLE TIME SCALES;WATER MANAGEMENT

Imitation with Intention and Memory: an Experiment

Three results emerge from a simple experiment on imitation. First, I find behavior which strongly suggests an intention to imitate. Second, players im- itate successful other players rather than repeating successful actions. Third, to find imitation examples, players use several periods of memory. This lends support to learning models with a non-trivial role of memory. The experiment analyzes imitation in an individual learning context. It sup- plements the results obtained for imitation in evolutionary processes.Imitation, Learning, Memory, Experiments

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

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