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Human cognition and emotion can be affected by subliminal visual stimulus. Does sustained subliminal auditory stimulus (SAS) have the similar effect? In this study, the speech sound “Be happier” was used as the SAS, and the power-to-take game was used as the experimental task to investigate the effect of SAS on human emotion. 34 subjects were randomly divided into control group and experiment group...
With some exceptions, current robotic systems need to be explicitly commanded for interactive tasks with humans. This constraint leads to a reduction in robot-human system level capabilities due to a lack of common grounding, and in addition, the robotic systems are selfcontained with little or no “social” intelligence. A cognitive architecture embodies robotic behaviors and the logical analysis of...
This research is aimed at achieving human consciousness in a robot. The authors focus on mirror image cognition, which is a high-level conscious function of humans, and have been conducting mirror image cognition tests with the robot, and have discovered that emotion and feelings are closely related to decision-making and learning. However, do humans always decide on an action through their emotions?...
Understanding how humans recognize face sketches drawn by artists is of significant value to both criminal investigators and researchers in computer vision, face biometrics and cognitive psychology. However, large scale experimental studies of hand-drawn face sketches are still very limited in terms of the number of artists, the number of sketches, and the number of human evaluators involved. In this...
Risk cubes, actually a 5×5 matrix, used in industry characterize particular risks in terms of the likelihood of occurrence, and the consequence of the actualized risk. Human cognitive bias research led by Daniel Kahneman and Amos Tversky exposed systematic translations of objective probability and value as judged by human subjects. An examination of industry-generated risk cube data reveals evidence...
The Immersive Naval Officer Training System (INOTS) is a blended learning environment that merges traditional classroom instruction with a mixed reality training setting. INOTS supports the instruction, practice and assessment of interpersonal communication skills. The goal of INOTS is to provide a consistent training experience to supplement interpersonal skills instruction for Naval officer candidates...
This paper presents the combination of electroencephalogram (EEG) power spectrum ratio and Spectral Centroids techniques to extract unique features for human stress from EEG signals. The combination of these techniques was able to improve the k-NN (k-Nearest Neighbor) classifier accuracy to detect and classify human stress from two cognitive states, Close-eye (CE) and Open-eye (OE). The EEG power...
The process of human's blink expressing deep information of mind has uncertainties of fuzziness and randomness. A cloud theory-based method is proposed to realize uncertainty control of virtual human's blink. Eyes' maximal open angle cloud and blink interval cloud are designed. A cloud-based blink control algorithm is proposed. Results of comparing it with certainty method show that the proposed algorithm...
This paper provides a general overview of the interdisciplinary study of cognitive science, specifically the area of the field involving artificial intelligence. In addition, the paper will elaborate on current research for cognitive science artificial intelligence, highlight the importance of this research by providing specific examples of its applications in present society, and briefly discuss...
A good data corpus lies at the heart of progress in both perceptual/cognitive science and in computer vision. While there are a few datasets that deal with simple actions, creating a realistic corpus for complex, long action sequences that contains also human-human interactions has so far not been attempted to our knowledge. Here, we introduce such a corpus for (inter)action understanding that contains...
While most activity recognition systems rely on data-driven approaches, the use of knowledge-driven techniques is gaining increasing interest. Research in this field has mainly concentrated on the use of ontologies to specify the semantics of activities, and ontological reasoning to recognize them based on context information. However, at the time of writing, the experimental evaluation of these techniques...
Motion databases have a strong potential to guide progress in the field of machine recognition and motion-based animation. Existing databases either have a very loose structure that does not sample the domain according to any controlled methodology or too few action samples which limits their potential to quantitatively evaluate the performance of motion-based techniques. The controlled sampling of...
Establishing correspondences across structural and functional brain images via labeling, or parcellation, is an important and challenging task for clinical neuroscience and cognitive psychology. A limitation with existing approaches is that they i) possess shallow architectures, ii) are based on heuristic manual feature engineering, and iii) assume the validity of the designed feature model. In contrast,...
Decoding perceptual or cognitive states based on brain activity measured using functional Magnetic Resonance Imaging (fMRI) can be achieved using machine learning algorithms to train classifiers of specific stimuli. However, the high dimensionality and intrinsically low Signal-to-Noise Ratio (SNR) of fMRI data poses great challenges to such techniques. The problem is aggravated in the case of multiple...
The concept of situation is central to the decision making processes of both human and software agents. The recognition of situation facilitates decision processes that ultimately result in action selection. Cognitive agent architectures that incorporate the concept of situation provide the opportunity for more sophisticated representations of human behavior and for more sophisticated decision support...
We investigated the effects of a decision aid designed to support the development of effective long term strategies when seeking to influence a complex adaptive system. The experiment compared a test condition with feedforward support (i.e., outcome projection) against a baseline condition both in terms of cognitive processing and goal attainment (i.e., strategy efficiency). Results show that the...
The application of techniques from artificial intelligence, human decision-making processes, optimization, and learning methodologies have led to significant development in the field of cognitive radios. A cognitive radio improves on a traditional radio by incorporating situational awareness, learning, and decision-making to meet the application goals and adapt to the current operating environment...
Classical models of Situation Awareness (SA) describe it as a process involving self-agency, or as rooted in [externally directed] consciousness operating in a perceptual cycle. These models are robust for dynamic situations where events unfold gradually in the temporal dimension at a rate that is compatible with the ability of the human agent to process information, and where this information processing...
This research focuses on applying both Scenario Planning and Multicriteria Decision Analysis (MCDA) approaches that have a great potential to support Strategic Decision Making. These methods make possible to assess strategic lines of action and to treat uncertainty related to future states. Considering a military context where there is an imminent catastrophic situation, this work demonstrates the...
An essential part in the construction of a mental picture of a situation is our ability to represent, assess and judge on the skill and competency level of a player, an agent, or any entity that makes decisions. Augmented with a suitable reasoning framework, this ability would allow us to diagnose the competency level of a player through real-time monitoring of their actions. The first key question...
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