Individual data analysis and Unified Theories of Cognition: A methodological proposal

Unified theories regularly appear in psychology. They also regularly fail to fulfil all of their goals. Newell (1990) called for their revival, using computer modelling as a way to avoid the pitfalls of previous attempts. His call, embodied in the Soar project has so far, however, failed to produce the breakthrough it promised. One of the reasons for the lack of success of Newell’s approach is that the methodology commonly used in psychology, based on controlling potentially confounding variables by using group data, is not the best way forward for developing unified theories of cognition. Instead, we propose an approach where (a) the problems related to group averages are alleviated by analysing subjects individually; (b) there is a close interaction between theory building and experimentation; and (c) computer technology is used to routinely test versions of the theory on a wide range of data. The advantages of this approach heavily outweigh the disadvantages

Memory pattern identification for feedback tracking control in human-machine systems

Objective: The aim of this paper was to identify the characteristics of memory patterns with respect to a visual input, perceived by the human operator during a manual control task, which consisted in following a moving target on a display with a cursor.Background: Manual control tasks involve nondeclarative memory. The memory encodings of different motor skills have been referred to as procedural memories. The procedural memories have a pattern, which this paper sought to identify for the particular case of a onedimensional tracking task. Specifically, data recorded from human subjects controlling dynamical systems with different fractional order were investigated.Method: A Finite Impulse Response (FIR) controller was fitted to the data, and pattern analysis was performed to the fitted parameters. Then, the FIR model was further reduced to a lower order controller; from the simplified model, the stability analysis of the human-machine system in closedloop was conducted.Results: It is shown that the FIR model can be employed to identify and represent patterns in human procedural memories during manual control tasks. The obtained procedural memory pattern presents a time scale of about 650 ms before decay. Furthermore, the fitted controller is stable for systems with fractional order less or equal to 1.Conclusion: For systems of different fractional order, the proposed control scheme – based on a FIR model – can effectively characterize the linear properties of manual control in humans.Application: This research supports a biofidelic approach to human manual control modeling over feedback visual perceptions. Relevant applications of this research are: the development of shared-control systems, where a virtual human model assists the human during a control task, and human operator state monitoring.</div

Modèles psychophysiques d'atteintes de cibles pour les personnes souffrant de troubles neuromusculaires

The studies on able-bodies showed that the text input is faster with physical AZERTY keyboard (75 Words Per Minute) than with virtual AZERTY keyboard with pointing (25 Words Per Minute). This reduction of speed is also observed during text input activity by disabled people with the UKO ambiguous keyboard. On the contrary, other studies show the benefits of optimizing the layout of the keys for the text input, under conditions of mobility for the OPTI and Metropolis keyboard and in office situation for the GAG keyboard.Thus, to understand and describe the motor deficiencies, we need to study the motor activity by applying the psychomotor law.This study have a double issue (theoretical and technological interest): the understanding of the motor deficiencies and the design of systems (such as virtual keyboards) based on interaction techniques of pointing.The objective is to propose a modeling of motor performances (and eventually perceptual performances) of our study population to predict the time necessary to move and to research targets. To achieve this goal, we studied the reaching of targets with 1 dimension. These models are then applied to study the usability of a software keyboard.Des études sur des personnes valides montrent que la saisie est plus rapide sur un clavier physique de type AZERTY (75 mots par minute) plutôt que sur un clavier virtuel de type AZERTY par désignation (25 mots par minute). Cette réduction de vitesse est aussi observée lors d'activités de saisie par des personnes handicapées avec le clavier ambigu UKO. Au contraire, d'autres travaux ont montré l'apport de l'optimisation de l'agencement spatial des touches pour la saisie, en situation de mobilité pour le clavier OPTI et le clavier Metropolis et en situation de bureau pour le clavier GAG.Ainsi, pour comprendre et qualifier ces troubles moteurs, nous avons besoin d'étudier les activités motrices en situation en appliquant la loi de psychomotricité. Cette étude a un double enjeu (intérêt théorique et technologique) : la compréhension des troubles moteurs et la conception des systèmes de suppléance (tels que les claviers virtuels) fondés sur des techniques d'interaction de pointage. L'objectif est de proposer une modélisation des performances motrices (et perceptives à termes) de notre population d'étude pour prédire le temps de déplacement et de recherche de cibles. Pour atteindre cet objectif, nous avons étudié l'atteinte de cibles à 1 dimension. Ces modèles sont ensuite appliqués à l'étude de l'utilisabilité d'un clavier logiciel

On emotion, learning and uncertainty: a cognitive modelling approach

A problem of emotion and cognition is considered within a unified theory of cognition. There is a strong case for modern cognitive models to take arousal component of emotion into account because of its significant influence on performance (e.g. the inverted-U effect). Several hypotheses have been proposed to explain this effect, but they have not been integrated into cognitive architectures. Based on the analysis of the ACT-R (Anderson & Lebiere, 1998) cognitive architecture the mechanisms that can be used to model this effect are identified. Then a model of the classical Yerkes and Dodson experiment is introduced. The model matches the data by modifying several parameters, particularly noise and goal value in the conflict resolution strategy. Thus, the model supports the idea that the character of decision making changes for different arousal and motivational states. The effect of these changes on learning is analysed using information theory. In particular, randomness in behaviour due to a noise increase leads to a faster entropy reduction. Thus, noise can improve learning in the initial stage of problem exploration or upon changes in the environment. Furthermore, dynamic motivation can optimise the expenditure of effort. Therefore, emotion may play an important role in adaptation of cognitive processes. It is argued that the current conflict resolution mechanism in ACT-R does not explain the dynamics suggested by the model. A new theory and algorithm are proposed that use posterior estimation of expected costs. There are three main contributions of the thesis: 1) Ways of including the effects of emotion and motivation into cognitive models; 2) The analysis of the role of emotion in learning and intelligence; and 3) The introduction of a new machine learning algorithm suitable for applications not only in cognitive modelling, but in other areas of computer science

Apport d'une conception centrée utilisateur adaptée selon les besoins des personnes en situation de handicap

Les personnes en situation de handicap moteur des membres supérieurs ont besoin de système de suppléance pour leur autonomie. Cependant 1/3 de ces aides de compensation sont abandonnées car pas encore suffisamment centrées sur les besoins et les aptitudes de l'utilisateur. La problématique centrale de cette thèse concerne la mise en œuvre d'une méthode de conception centrée utilisateur, adaptée en fonction de la population d'études (personnes en situation de handicap ayant des troubles neuro-moteurs langagiers) pour la conception de trois aides de compensation. La première concerne la commande d'un bras robotique de préhension JACO pour laquelle la conception centrée utilisateur classique a été appliquée. Celle-ci est adaptée pour les personnes pouvant s'exprimer oralement mais qu'en est-il lorsque ces personnes ne peuvent participer directement ou bien ont besoin de leurs aidants pour exprimer leurs besoins ou répondre aux questionnaires? Une alternative est de recueillir les besoins par l'intermédiaire d'experts. Nous montrerons comment la méthode de conception centrée utilisateur a été adaptée pour la conception du système HandiMathKey pour la saisie de formules Mathématiques. Notre dernière adaptation est d'utiliser l'écosystème de la personne comme médiateur pour communiquer et un profil utilisateur. Cette méthode a permis de concevoir l'interface de communication intégrée et de contrôle d'environnement nommée CECI. Nous décrirons également comment la plateforme SoKeyTo permet le prototypage des aides de compensation. Pour chacune des aides de compensation, nous rapporterons les évaluations réalisées et nous discuterons la manière dont la méthode de conception a été adaptée.People with motor impairment of the upper limbs need an assistive technology for their autonomy. However, 1/3 of these assistive technologies are abandoned because they are not yet sufficiently focused on the needs and abilities of the user. The central problem of this thesis concerns the implementation of a user-centered design method adapted to the study population (persons with disabilities with neuro-motor language impairments) for the design of three applications. The first concerns the control of a robot arm JACO for which the classic user centered design has been applied. This is appropriate for people who can speak orally, but what if they cannot participate directly or need their caregivers to express their needs or answer questionnaires? An alternative is to gather needs through experts. We will show how the user centered design method has been adapted for the design of the HandiMathKey system for entering mathematical formulas. Our last adaptation is to use the person's ecosystem as a mediator to communicate and a user profile. This method allowed to design the integrated communication and environmental control interface named CECI. We will also describe how the SoKeyTo platform allows prototyping of assistive technologies. For each of the assistive technologies, we will report the assessments made and discuss how the design method has been adapted

On emotion, learning and uncertainty: a cognitive modelling approach

A problem of emotion and cognition is considered within a unified theory of cognition. There is a strong case for modern cognitive models to take arousal component of emotion into account because of its significant influence on performance (e.g. the inverted-U effect). Several hypotheses have been proposed to explain this effect, but they have not been integrated into cognitive architectures. Based on the analysis of the ACT-R (Anderson & Lebiere, 1998) cognitive architecture the mechanisms that can be used to model this effect are identified. Then a model of the classical Yerkes and Dodson experiment is introduced. The model matches the data by modifying several parameters, particularly noise and goal value in the conflict resolution strategy. Thus, the model supports the idea that the character of decision making changes for different arousal and motivational states. The effect of these changes on learning is analysed using information theory. In particular, randomness in behaviour due to a noise increase leads to a faster entropy reduction. Thus, noise can improve learning in the initial stage of problem exploration or upon changes in the environment. Furthermore, dynamic motivation can optimise the expenditure of effort. Therefore, emotion may play an important role in adaptation of cognitive processes. It is argued that the current conflict resolution mechanism in ACT-R does not explain the dynamics suggested by the model. A new theory and algorithm are proposed that use posterior estimation of expected costs. There are three main contributions of the thesis: 1) Ways of including the effects of emotion and motivation into cognitive models; 2) The analysis of the role of emotion in learning and intelligence; and 3) The introduction of a new machine learning algorithm suitable for applications not only in cognitive modelling, but in other areas of computer science