2,515 research outputs found

    Computational Models of Consciousness-Emotion Interactions in Social Robotics: Conceptual Framework

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    There is a little information on how to design a social robot that effectively executes consciousness-emotion (C-E) interaction in a socially acceptable manner. In fact, development of such socially sophisticated interactions depends on models of human high-level cognition implemented in the robot’s design. Therefore, a fundamental research problem of social robotics in terms of effective C-E interaction processing is to define a computational architecture of the robotic system in which the cognitive-emotional integration occurs and determine cognitive mechanisms underlying consciousness along with its subjective aspect in detecting emotions. Our conceptual framework rests upon assumptions of a computational approach to consciousness, which points out that consciousness and its subjective aspect are specific functions of the human brain that can be implemented into an artificial social robot’s construction. Such research framework of developing C-E addresses a field of machine consciousness that indicates important computational correlates of consciousness in such an artificial system and the possibility to objectively describe such mechanisms with quantitative parameters based on signal-detection and threshold theories

    Active Learning: Effects of Core Training Design Elements on Self-Regulatory Processes, Learning, and Adaptability

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    This research describes a comprehensive examination of the cognitive, motivational, and emotional processes underlying active learning approaches, their effects on learning and transfer, and the core training design elements (exploration, training frame, emotion-control) and individual differences (cognitive ability, trait goal orientation, trait anxiety) that shape these processes. Participants (N = 350) were trained to operate a complex computer-based simulation. Exploratory learning and error-encouragement framing had a positive effect on adaptive transfer performance and interacted with cognitive ability and dispositional goal orientation to influence trainees’ metacognition and state goal orientation. Trainees who received the emotion-control strategy had lower levels of state anxiety. Implications for developing an integrated theory of active learning, learner-centered design, and research extensions are discussed

    Motivations, Values and Emotions: 3 sides of the same coin

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    This position paper speaks to the interrelationships between the three concepts of motivations, values, and emotion. Motivations prime actions, values serve to choose between motivations, emotions provide a common currency for values, and emotions implement motivations. While conceptually distinct, the three are so pragmatically intertwined as to differ primarily from our taking different points of view. To make these points more transparent, we briefly describe the three in the context a cognitive architecture, the LIDA model, for software agents and robots that models human cognition, including a developmental period. We also compare the LIDA model with other models of cognition, some involving learning and emotions. Finally, we conclude that artificial emotions will prove most valuable as implementers of motivations in situations requiring learning and development

    IDA: A Cognitive Agent Architecture

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    Higher-level Knowledge, Rational and Social Levels Constraints of the Common Model of the Mind

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    In his famous 1982 paper, Allen Newell [22, 23] introduced the notion of knowledge level to indicate a level of analysis, and prediction, of the rational behavior of a cognitive articial agent. This analysis concerns the investigation about the availability of the agent knowledge, in order to pursue its own goals, and is based on the so-called Rationality Principle (an assumption according to which "an agent will use the knowledge it has of its environment to achieve its goals" [22, p. 17]. By using the Newell's own words: "To treat a system at the knowledge level is to treat it as having some knowledge, some goals, and believing it will do whatever is within its power to attain its goals, in so far as its knowledge indicates" [22, p. 13]. In the last decades, the importance of the knowledge level has been historically and system- atically downsized by the research area in cognitive architectures (CAs), whose interests have been mainly focused on the analysis and the development of mechanisms and the processes governing human and (articial) cognition. The knowledge level in CAs, however, represents a crucial level of analysis for the development of such articial general systems and therefore deserves greater research attention [17]. In the following, we will discuss areas of broad agree- ment and outline the main problematic aspects that should be faced within a Common Model of Cognition [12]. Such aspects, departing from an analysis at the knowledge level, also clearly impact both lower (e.g. representational) and higher (e.g. social) levels

    Consciousness and Social Cognition from an Interactionist Perspective: A New Approach on Understanding Normal and Abnormal Relations between Metacognition and Mindreading

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    Contemporary discussions on relations between metacognition and mindreading result in several theoretical accounts allowing various combinations of both mechanisms in the process of formation of beliefs, intentions, and decisions with respect to oneself or others. In fact, various prefrontal areas of the brain are activated when individuals mentalize about themselves and about other people. Interestingly, the latest accounts of the relationship between mindreading and metacognition clearly favor arguments for interactionism between functionally different mechanisms in the formation of our social knowledge. In particular, a two-level architecture enables a mutual interaction within a complex metacognitive system that is evolutionarily structured into higher and lower level metacognition with different functions and tasks. In our opinion, cognitive architecture of such systems needs to include conscious mechanisms that incorporate information accessibility as activation through the interaction. Here, we will argue that the combination of the two-level account on mindreading and metacognition along with a global broadcasting architecture embedded in the human brain is a good starting point that explains formation of accurate social knowledge and access to such knowledge. In our opinion, it becomes clear that consciousness via the interaction activates many unconscious brain regions, including interpreter systems such as metacognition and mindreading

    A Higher-Order Theory of Emotional Consciousness

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    Emotional states of consciousness, or what are typically called emotional feelings, are traditionally viewed as being innately programed in subcortical areas of the brain, and are often treated as different from cognitive states of consciousness, such as those related to the perception of external stimuli. We argue that conscious experiences, regardless of their content, arise from one system in the brain. On this view, what differs in emotional and non-emotional states is the kind of inputs that are processed by a general cortical network of cognition, a network essential for conscious experiences. Although subcortical circuits are not directly responsible for conscious feelings, they provide non-conscious inputs that coalesce with other kinds of neural signals in the cognitive assembly of conscious emotional experiences. In building the case for this proposal, we defend a modified version of what is known as the higher-order theory of consciousness

    A Multilevel Analysis of the Effect of Prompting Self-Regulation in Technology-Delivered Instruction

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    We used a within-subjects design and multilevel modeling in two studies to examine the effect of prompting self-regulation, an intervention designed to improve learning from technology-delivered instruction. The results of two studies indicate trainees who were prompted to self-regulate gradually improved their knowledge and performance over time, relative to the control condition. In addition, Study 2 demonstrated that trainees’ cognitive ability and self-efficacy moderated the effect of the prompts. Prompting self-regulation resulted in stronger learning gains over time for trainees with higher ability or higher self-efficacy. Overall, the two studies demonstrate that prompting self-regulation had a gradual, positive effect on learning, and the strength of the effect increased as trainees progressed through training. The results are consistent with theory suggesting self-regulation is a cyclical process that has a gradual effect on learning and highlight the importance of using a within-subjects design in self-regulation. research

    Building Life-Like “Conscious” Software Agents

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    Action Selection and Language Generation in “Conscious” Software Agents

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