4,610 research outputs found

    Cognitive modeling of social behaviors

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    To understand both individual cognition and collective activity, perhaps the greatest opportunity today is to integrate the cognitive modeling approach (which stresses how beliefs are formed and drive behavior) with social studies (which stress how relationships and informal practices drive behavior). The crucial insight is that norms are conceptualized in the individual mind as ways of carrying out activities. This requires for the psychologist a shift from only modeling goals and tasks —why people do what they do—to modeling behavioral patterns—what people do—as they are engaged in purposeful activities. Instead of a model that exclusively deduces actions from goals, behaviors are also, if not primarily, driven by broader patterns of chronological and located activities (akin to scripts). To illustrate these ideas, this article presents an extract from a Brahms simulation of the Flashline Mars Arctic Research Station (FMARS), in which a crew of six people are living and working for a week, physically simulating a Mars surface mission. The example focuses on the simulation of a planning meeting, showing how physiological constraints (e.g., hunger, fatigue), facilities (e.g., the habitat’s layout) and group decision making interact. Methods are described for constructing such a model of practice, from video and first-hand observation, and how this modeling approach changes how one relates goals, knowledge, and cognitive architecture. The resulting simulation model is a powerful complement to task analysis and knowledge-based simulations of reasoning, with many practical applications for work system design, operations management, and training

    Human-Machine Communication: Complete Volume. Volume 6

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    his is the complete volume of HMC Volume 6

    MULTI-MODAL TASK INSTRUCTIONS TO ROBOTS BY NAIVE USERS

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    This thesis presents a theoretical framework for the design of user-programmable robots. The objective of the work is to investigate multi-modal unconstrained natural instructions given to robots in order to design a learning robot. A corpus-centred approach is used to design an agent that can reason, learn and interact with a human in a natural unconstrained way. The corpus-centred design approach is formalised and developed in detail. It requires the developer to record a human during interaction and analyse the recordings to find instruction primitives. These are then implemented into a robot. The focus of this work has been on how to combine speech and gesture using rules extracted from the analysis of a corpus. A multi-modal integration algorithm is presented, that can use timing and semantics to group, match and unify gesture and language. The algorithm always achieves correct pairings on a corpus and initiates questions to the user in ambiguous cases or missing information. The domain of card games has been investigated, because of its variety of games which are rich in rules and contain sequences. A further focus of the work is on the translation of rule-based instructions. Most multi-modal interfaces to date have only considered sequential instructions. The combination of frame-based reasoning, a knowledge base organised as an ontology and a problem solver engine is used to store these rules. The understanding of rule instructions, which contain conditional and imaginary situations require an agent with complex reasoning capabilities. A test system of the agent implementation is also described. Tests to confirm the implementation by playing back the corpus are presented. Furthermore, deployment test results with the implemented agent and human subjects are presented and discussed. The tests showed that the rate of errors that are due to the sentences not being defined in the grammar does not decrease by an acceptable rate when new grammar is introduced. This was particularly the case for complex verbal rule instructions which have a large variety of being expressed

    The Media Inequality, Uncanny Mountain, and the Singularity is Far from Near: Iwaa and Sophia Robot versus a Real Human Being

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    Design of Artificial Intelligence and robotics habitually assumes that adding more humanlike features improves the user experience, mainly kept in check by suspicion of uncanny effects. Three strands of theorizing are brought together for the first time and empirically put to the test: Media Equation (and in its wake, Computers Are Social Actors), Uncanny Valley theory, and as an extreme of human-likeness assumptions, the Singularity. We measured the user experience of real-life visitors of a number of seminars who were checked in either by Smart Dynamics' Iwaa, Hanson's Sophia robot, Sophia's on-screen avatar, or a human assistant. Results showed that human-likeness was not in appearance or behavior but in attributed qualities of being alive. Media Equation, Singularity, and Uncanny hypotheses were not confirmed. We discuss the imprecision in theorizing about human-likeness and rather opt for machines that 'function adequately.

    Self-Adaptive Communication for Collaborative Mobile Entities in ERCMS

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    International audienceAdaptation of communication is required for maintaining the connectivity and the quality of communication in group-wide collaborative activities. This becomes challenging to handle when considering mobile entities in a wireless environment, requiring responsiveness and availability of the communication system. We address these challenges in the context of the ROSACE project where mobile ground and flying robots have to collaborate with each other and with remote human and artificial actors to save and rescue in case of disasters such as forest fires. This paper aims to expose a communication component architecture allowing to manage a cooperative adaptation which is aware of the activity and resource context into pervasive environment. This allows to provide the appropriate adaptation of the activity in response to evolutions of the activity requirements and the changes in relation with the communication resource constraints. In this paper, we present a simulation of a ROSACE use case. The results show how ROSACE entities collaborate to maintain the connectivity and to enhance the quality of communications

    Virtual Reality Games for Motor Rehabilitation

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    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

    2019 Symposium on Education in Entertainment and Engineering

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