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Auflistung nach Autor:in "Hamker, Fred H."

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  • Zeitschriftenartikel
    A Neuroscientific View on the Role of Emotions in Behaving Cognitive Agents
    (KI - Künstliche Intelligenz: Vol. 25, No. 3, 2011) Vitay, Julien; Hamker, Fred H.
    While classical theories systematically opposed emotion and cognition, suggesting that emotions perturbed the normal functioning of the rational thought, recent progress in neuroscience highlights on the contrary that emotional processes are at the core of cognitive processes, directing attention to emotionally-relevant stimuli, favoring the memorization of external events, valuating the association between an action and its consequences, biasing decision making by allowing to compare the motivational value of different goals and, more generally, guiding behavior towards fulfilling the needs of the organism. This article first proposes an overview of the brain areas involved in the emotional modulation of behavior and suggests a functional architecture allowing to perform efficient decision making. It then reviews a series of biologically-inspired computational models of emotion dealing with behavioral tasks like classical conditioning and decision making, which highlight the computational mechanisms involved in emotional behavior. It underlines the importance of embodied cognition in artificial intelligence, as emotional processing is at the core of the cognitive computations deciding which behavior is more appropriate for the agent.
  • Zeitschriftenartikel
    Human Capacities for Emotion Recognition and their Implications for Computer Vision
    (i-com: Vol. 14, No. 2, 2015) Liebold, Benny; Richter, René; Teichmann, Michael; Hamker, Fred H.; Ohler, Peter
    Current models for automated emotion recognition are developed under the assumption that emotion expressions are distinct expression patterns for basic emotions. Thereby, these approaches fail to account for the emotional processes underlying emotion expressions. We review the literature on human emotion processing and suggest an alternative approach to affective computing. We postulate that the generalizability and robustness of these models can be greatly increased by three major steps: (1) modeling emotional processes as a necessary foundation of emotion recognition; (2) basing models of emotional processes on our knowledge about the human brain; (3) conceptualizing emotions based on appraisal processes and thus regarding emotion expressions as expressive behavior linked to these appraisals rather than fixed neuro-motor patterns. Since modeling emotional processes after neurobiological processes can be considered a long-term effort, we suggest that researchers should focus on early appraisals, which evaluate intrinsic stimulus properties with little higher cortical involvement. With this goal in mind, we focus on the amygdala and its neural connectivity pattern as a promising structure for early emotional processing. We derive a model for the amygdala-visual cortex circuit from the current state of neuroscientific research. This model is capable of conditioning visual stimuli with body reactions to enable rapid emotional processing of stimuli consistent with early stages of psychological appraisal theories. Additionally, amygdala activity can feed back to visual areas to modulate attention allocation according to the emotional relevance of a stimulus. The implications of the model considering other approaches to automated emotion recognition are discussed.
  • Zeitschriftenartikel
    Neural Learning of Cognitive Control
    (KI - Künstliche Intelligenz: Vol. 26, No. 4, 2012) Hamker, Fred H.
    Our goal is to develop cognitive agents based on neuroscientific evidence. The efficiency of cognitive behavior depends on its capacity to select, represent and manipulate sufficient knowledge of the environment to achieve its goals. We designed a biologically motivated model of basal ganglia and particularly the prefrontal cortex and here review its foundations of neural learning and summarize our obtained results.