Abstract: Computer-Assisted Instruction systems (CAI) enable fully automated simulator-based training. Traditionally, a CAI system does not enable a true dialogue between the learner and the virtual instructor. Most frequently, the system acts like a human expert, and authoritatively provides feedback and ways to improve the task performance. In this conference paper, we describe an educational agent that enables a dialogue between the learner and the agent. The agent is called the companion agent. It acts like a virtual co-learner, for example by deliberating about new operational measures after a situation-change. The agent operates on the same authority level as the learner, and is therefore less threatening than a traditional virtual instructor. We believe companion agents are typically useful in modern, constructive learning situations where learners can take control of their own learning process. Potential applications of companion agents lie within the civil area (for example a civil tunnel operator during tunnel surveillance training) and the military area (for example embedded training in tactical surveillance).
This paper was selected as one of the Continuing Education Unit (CEU) papers for the 2007 Interservice/Industry Training, Simulation and Education Conference (I/ITSEC). The I/ITSEC board states that only those papers that demonstrate exceptional innovation, research, experimentation, and documentation in an area of new technology are selected for CEU credit.
Abstract: Abstract: Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents.
Because exact RL can only be applied to very simple problems, approximate algorithms are
usually necessary in practice. Many algorithms for approximate RL rely on basis-function
representations of the value function (or of the Q-function). Designing a good set of basis
functions without any prior knowledge of the value function (or of the Q-function) can be a
diﬃcult task. In this paper, we propose instead a technique to optimize the shape of a constant
number of basis functions for the approximate, fuzzy Q-iteration algorithm. In contrast to other
approaches to adapt basis functions for RL, our optimization criterion measures the actual
performance of the computed policies in the task, using simulation from a representative set
of initial states. A complete algorithm, using cross-entropy optimization of triangular fuzzy
membership functions, is given and applied to the car-on-the-hill example.
Abstract: This paper concerns the practical measurement of vigilance in a working environment. Vigilance can be measured in a number of ways, of which the electroencephalogram (EEG) is probably the most popular. However, the EEG method is not practical in a dynamic work setting for a number of reasons. This paper introduces a technique for assessing vigilance by means of easy-to-use and sensitive objective (performance) and subjective (questionnaire) behavioral measures. This technique does not include predefined or specified tasks, but a general principle of assessment. Vigilance assessment can be achieved by administering a vigilance test battery that includes a short working memory task and a short questionnaire. In situations that do not allow presentation of test batteries, both vigilance and the degree of (under-) stimulation can be assessed by performance on work-embedded tasks. This, however, requires analysis of the task set for a given job. It is discussed with what parameters a measurement technique needs to be described in order to determine exactly which measure(s) to use in a particular situation.
Abstract: The system being described in the paper presents a Web interface for a fully automatic audio-video human emotion recognition. The analysis is focused on the set of six basic emotions plus the neutral type. Different classifiers are involved in the process of face detection (AdaBoost), facial expression recognition (SVM and other models) and emotion recognition from speech (GentleBoost). The Active Appearance Model - AAM is used to get the information related to the shapes of the faces to be analyzed. The facial expression recognition is frame based and no temporal patterns of emotions are managed. The emotion recognition from movies is done separately on sound and video frames. The algorithm does not handle the dependencies between audio and video during the analysis. The methodologies for data processing are explained and specific performancemeasures for the emotion recognition are presented.
Abstract: The term vigilance is used frequently in a wide variety of research areas. The British neurologist Sir Henry Head introduced the term to refer to a state of high consciousness. Nowadays, ‘vigilance’ is used in neurophysiological research, but also in the experimental psychological field. Related terms, such as arousal, sustained attention, and tonic alertness are often used jointly with or instead of the term vigilance. It may seem that all these designations can be interchanged freely, but this is not the case. Many investigators differentiate these terms and the distinctions made are not always subtle. The terminological confusion of vigilance involves on the one hand its definition (i.e. clarification of the theoretical construct) with reference to different processes, and on the other hand different measuring procedures. The original definition of vigilance: “… a high state of physiological efficiency” is rather physiological in nature, but the “efficiency” part points to behavior. Head’s clarification that a vigilant state differs from a pure condition of raised excitability appears to be of major importance. The combination of physiological activity and efficient behavior is of great relevance and underlines the difference between vigilance and more basic energetic conditions.
The topic of this paper is the exploration of procedures for measuring vigilance. EEG-measures are very popular and are described first. More specifically, the spectral content of the EEG is investigated. Second, behavioral measures are presented. These concern performance on vigilance tasks. Finally, subjective questionnaires are explored.