This thesis investigates the design of sociable technologies and is divided into three main parts described below. In the first part, we introduce sociable technologies. We review our the definition of technology and propose categories of technologies according to the motivation underlying their design: improvement of control, improvement of communication or improvement of cooperation. Sociable technologies are then presented as an extension of techniques to improve cooperation. The design of sociable technologies are then discussed leading to the observation that acquisition of social common sense is a key challenge for designing sociable technologies. Finally, polite technologies are presented as an approach for acquiring social common sense. In the second part, we focus on the premises for the design of sociable technologies. A key aspect of social common sense is the ability to act appropriately in social situations. Associating appropriate behaviour with social situations is presented as a key method for implementing polite technologies. Reinforcement learning is proposed as a method for learning such associations and variation of this algorithm are experimentally evaluated. Learning the association between situation and behaviour relies on the strong assumption that mutual understanding of social situations can be achieved between technologies and people during interaction. We argue that in order to design sociable technologies, we must change the model of communication used by our technologies. We propose to replace the well-known code model of communication, with the ostensive-inferential model proposed by Sperber and Wilson. Hypotheses raised by this approach are evaluated in an experiment conducted in a smart environment, where, subjects by group of two or three are asked to collaborate with a smart environment in order to teach it how to behave in an automated meeting. A novel experimental methodology is presented: The Sorceress of Oz. The results collected from this experiment validate our hypothesis and provide insightful information for the design. We conclude by presenting, what we believe are, the premises for the design of sociable technologies. The final part of the thesis concerns an infrastructure for the design of sociable technologies. This infrastructure provides the support for three fundamental components. First, it provides the support for an inferential model of context. This inferential model of context is presented; a software architecture is proposed and evaluated in an experiment conducted in a smart-environment. Second, it provides the support for reasoning by analogy and introduces the concept of eigensituations. The advantage of this representation are discussed and evaluated in an experiment. Finally, it provides the support for ostensive-inferential communication and introduces the concept of ostensive interface.
OMiSCID 2.0 is a lightweight middleware for ubiquitous computing and ambient intelligence. Its main objective is to bring Service Oriented Architectures to all developers. After reviewing related works, we demonstrate how OMiSCID 2.0, compared to other available solutions, integrates easily in classical workflows without adding any constraints on the development process. A basic overview of our middleware is given along with brief technical descriptions demonstrating its User Friendly Application Programming Interface. This application programming interface makes it straightforward to expose, look for or send information between software components over the network. We illustrate the usage of OMiSCID 2.0, the new version of our lightweight middleware, through ase-studies that have been experienced in international research projects. Particularly, we demonstrate its advantages in both development and research projects, illustrating its radical cut down effect in development time, improving software reuse and easing redeployment notably in the context of Wizard of Oz experiments conducted in smart environments.
Abstract: We report on an empirical study aiming to analyze the importance of mutual understanding and shared context for human-computer social interaction. Subjects are asked to collaborate with a small robot in a smart environment. The Sorceress of Oz is presented as an alternative to the Wizard of Oz, and preliminary results are presented.
Abstract: We argue that current human-computer interaction model inherit from the so called “code model” of communication, that we state is keeping human-computer interaction to be natural and intuitive. We propose instead to consider another model inspired from current research in cognitive science and introduce the concept of ostensive interface that we believe is a key toward fluent human-computer interaction.
Abstract: We present an approach for acquiring common sense knowledge from social interaction. We argue that social common sense should be learned from daily interactions using implicit user's feedbacks and requires shared understanding of social situations. A service-oriented architecture, inspired from cognitive science, that foster mutual understanding between a smart environment and its inhabitants is presented. The method makes use of ConceptNet to work with common sense knowledge. We are able to successfully use and learn common sense knowledge.
Abstract: In this paper we present a situated end user programming approach where user co-constructs, in an iterative process, a mutual cognitive environment with the system. We argue that co-construction of a mutual cognitive environment, between both the human and the system, is a key toward social human-computer interaction. Preliminary results are illustrated with a step by step case study: a user teaches the system new perceptual and abstract concepts using hand gesture and an interactive learning table.
Abstract: This paper presents a case study of the usage of OMiSCID 2.0, the new version of a lightweight middleware for ubiquitous computing and ambient intelligence. The objective of this middleware is to bring Service Oriented Architectures to all developers. After comparing to available solutions, we show how it integrates in classical workflow without adding any constraint on the development process. Developers only need to use a library available in widely used programming languages (C++, Java and Python). Then, the basics of OMiSCID and a brief technical description are described as its User Friendly API. This API makes it straightforward to expose, look for or send messages between software components over a network. The added value of the proposed middleware has already been experienced in international research projects. This paper demonstrates its effect in cutting down development time, improving software reuse and easing redeployment in the context of a Wizard of Oz experiments in intelligent environments.
Abstract: Cet article présente OMiSCID et ses dernières évolutions vers la version 2.0. OMiSCID est un intergiciel facilitant le développement et le déploiement d'application réparties et notamment des applications ubiquitaires dans les environnements intelligents. OMiSCID est entièrement gratuit, libre et opensource avec une licence non collante de type. Il est utilisable avec plusieurs langages de programmation et sous différents systèmes d'exploitation. Son interface de programmation orientée utilisateur tend à fournir une simplicité d'utilisation maximale et une courbe d'apprentissage minimale. L'objectif de cet article est d'exposer les différentes fonctionnalités offertes par OMiSCID en illustrant son utilisation au travers d'exemples concrets. Nous présentons également OMiSCID GUI, une plateforme générique offrant une interface graphique facilitant le développement, le débuggage et la construction d'application.
Abstract: In this paper we describe the use of situation models for observing and understanding activity. Observing activity in natural environments can be an extremely complex perceptual problem. Situation models provide a means to both focus attention in such systems and to provide default reasoning to accommodate missing and erroneous observations. We briefly review the use of situations models in Cognitive Science and then describe how such models can be used to provide services based on observation of human activity. We present a layered component-oriented software architecture in which components for perception and action maintain a situation model for use in providing human services. We describe how this model can be used to observe activity.
Abstract: In this paper, we describe experiments with methods for learning the appropriateness of behaviors based on a model of the current social situation. We first review different approaches for social robotics, and present a new approach based on situation modeling. We then review algorithms for social learning and propose three modifications to the classical Q-Learning algorithm. We describe five experiments with progressively complex algorithms for learning the appropriateness of behaviors. The first three experiments illustrate how social factors can be used to improve learning by controlling learning rate. In the fourth experiment we demonstrate that proper credit assignment improves the effectiveness of reinforcement learning for social interaction. In our fifth experiment we show that analogy can be used to accelerate learning rates in contexts composed of many situations.