The emergence of mind and brain: an evolutionary, computational, and philosophical approach.
ABSTRACT Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.
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ABSTRACT: In the age of globalization, economic growth and the welfare of nations decisively depend on basic innovations. Therefore, education and knowledge is an important advantage of competition in highly developed countries with high standards of salaries, but raw material shortage. In the twenty-first century, innovations will arise from problem-oriented research, crossing over traditional faculties and disciplines. Therefore, we need platforms of interdisciplinary dialogue to choose transdisciplinary problems (e.g., environment, energy, information, health, welfare) and to cluster new portfolios of technologies. The clusters of research during the excellence initiative at German universities are examples of converging sciences. The integration of natural and engineering sciences as well as medicine can only be realized if the research training programs (e.g., graduate schools) generate a considerable added value in terms of multidisciplinary experience, international networking, scientific and entrepreneurial know-how, and personality development. The Carl von Linde-Academy is presented as an example of an interdisciplinary center of research and teaching at the Technical University of Munich.Poiesis & Praxis 06/2011; 7(4):275-289.
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ABSTRACT: The current paper is an investigation towards understanding the navigational performance of humans on a network when the "landmark" nodes are blocked. We observe that humans learn to cope up, despite the continued introduction of blockages in the network. The experiment proposed involves the task of navigating on a word network based on a puzzle called the wordmorph. We introduce blockages in the network and report an incremental improvement in performance with respect to time. We explain this phenomenon by analyzing the evolution of the knowledge in the human participants of the underlying network as more and more landmarks are removed. We hypothesize that humans learn the bare essentials to navigate unless we introduce blockages in the network which would whence enforce upon them the need to explore newer ways of navigating. We draw a parallel to human problem solving and postulate that obstacles are catalysts for humans to innovate techniques to solve a restricted variant of a familiar problem.04/2012;
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ABSTRACT: The ability to delegate control over repetitive tasks from higher to lower neural centers may be a fundamental innovation in human cognition. Plausibly, the massive neurocomputational challenges associated with the mastery of balance during the evolution of bipedality in proto-humans provided a strong selective advantage to individuals with brains capable of efficiently transferring tasks in this way. Thus, the shift from quadrupedal to bipedal locomotion may have driven the rapid evolution of distinctive features of human neuronal functioning. We review recent studies of functional neuroanatomy that bear upon this hypothesis, and identify ways to test our ideas.Frontiers in Neuroscience 01/2014; 8:90.