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Automation, robotics, brains, and a new theory of Physics Sergio Pissanetzky

1. Automation, robotics, brains, and a new theory of Physics Sergio Pissanetzky Sergio@SciControls.com. 2. C omplex systems with a detailed dynamics Too detailed for Statistical Mechanics or n on-linear Dynamics. Examples: -- adaptive systems: brain, organisms, organs, species.

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Automation, robotics, brains, and a new theory of Physics Sergio Pissanetzky

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  1. 1 Automation, robotics, brains, and a new theory of Physics Sergio Pissanetzky Sergio@SciControls.com

  2. 2 Complex systems with a detailed dynamics Too detailed for Statistical Mechanics or non-linear Dynamics. Examples: -- adaptive systems: brain, organisms, organs, species. -- robots, computers.

  3. 3 mother! adaptive system mother! ?

  4. scale-free hierarchical network 4

  5. 5 mother! mother

  6. 6 • Central Theorem • Any dynamical system has a scale-free hierarchical network of group-theoretical block systems that represents an invariant behavior of the system.

  7. 7 Scale-free hierarchical networks of information uncertainty, prediction, entropy, granularity prediction Causal set model – mathematical properties Action functional Theory of Causal Dynamical Systems complex systems with detailed dynamics, such as adaptive systems BOTTOM - UP Fundamental principles of Physics causality, symmetry, least-action, energy/entropy ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

  8. 8 TOP – DOWN ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// Neuro- science Artificial intelligence Computer engineering Physics Bio- physics Evolution observation verification Fuster Cuntz Friston Lin Eagleman Still (motor – proteins) Lerner Kauffman DNA Google patents OO A&D Shih Tsallis Pernu-Annila Hawkins George (Numenta) Natural languages heuristic theory Scale-free hierarchical networks of information uncertainty, prediction, entropy, granularity MOVEMENT? Scale-free hierarchical networks of information uncertainty, prediction, entropy, granularity prediction Causal set model – mathematical properties Action functional Theory of Causal Dynamical Systems complex systems with detailed dynamics, such as adaptive systems BOTTOM - UP Fundamental principles of Physics causality, symmetry, least-action, energy/entropy ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

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