The emergence of mind and brain: an evolutionary, computational, and philosophical approach
Chair for Philosophy of Science, Institute of Interdisciplinary Informatics, University of Augsburg, Augsburg, Germany. Progress in brain research
(Impact Factor: 2.83).
02/2008; 168:115-32. DOI: 10.1016/S0079-6123(07)68010-8
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.
Available from: Richard Shine
- "Importantly, this analogy is about function and not mechanism: we do not suggest that the computational algorithms used by the human brain are similar to those required for RAM and ROM. Indeed, it is far more likely, based on the precise connectivity of the human brain, that the process of " delegation " from goal-directed to habitual behavior emerges as a function of complex dynamics within neuronal networks (Weaver, 2005; Mainzer, 2008; Balsters et al., 2010; Hertel and Brozovich, 2010; Smaers et al., 2011, 2013). This analogy also suggests the intriguing possibility that subjective conscious experience is the " user interface " employed by an organism—and that delegation of processing enables us to be aware of (and thus, able to react to) only a small subset of issues (those which benefit from rapid flexible decision-making). "
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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 04/2014; 8(8):90. DOI:10.3389/fnins.2014.00090 · 3.66 Impact Factor
Available from: uaem.mx
- "According to the paradigm of complex dynamical systems (Mainzer, 2008), a robot can be described at different levels, in which global properties at one level emerge from the interaction of a number of simple elements at lower levels. Global properties are emergent in the sense that they result from nothing else but local interactions among the elements. "
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ABSTRACT: After an introduction (1) the article analyzes the evolution of the embodied mind (2), the innovation of embodied robotics (3), and finally discusses conclusions of embodied robotics for human responsibility (4). Considering the evolution of the embodied mind (2), we start with an introduction of complex systems and nonlinear dynamics (2.1), apply this approach to neural self-organization (2.2), distinguish degrees of complexity of the brain (2.3), explain the emergence of cognitive states by complex systems dynamics (2.4), and discuss criteria for modeling the brain as complex nonlinear system (2.5). The innovation of embodied robotics (3) is a challenge of future technology. We start with the distinction of symbolic and embodied AI (3.1) and explain embodied robots as dynamical systems (3.2). Self-organization needs self-control of technical systems (3.3). Cellular neural networks (CNN) are an example of self-organizing technical systems offering new avenues for neurobionics (3.4). In general, technical neural networks support different kinds of learning robots (3.5). Finally, embodied robotics aim at the development of cognitive and conscious robots (3.6).
Journal of Physiology-Paris 09/2009; 103(3-5):296-304. DOI:10.1016/j.jphysparis.2009.08.012 · 1.90 Impact Factor
Available from: PubMed Central
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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. DOI:10.1007/s10202-011-0088-8 · 0.13 Impact Factor
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