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  2. Cognitive robotics - Wikipedia

    en.wikipedia.org/wiki/Cognitive_robotics

    Cognitive robotics may be considered the engineering branch of embodied cognitive science and embodied embedded cognition, consisting of Robotic Process Automation, Artificial Intelligence, Machine Learning, Deep Learning, Optical Character Recognition, Image Processing, Process Mining, Analytics, Software Development and System Integration.

  3. Category:Robotics templates - Wikipedia

    en.wikipedia.org/wiki/Category:Robotics_templates

    If the template has a separate documentation page (usually called "Template:template name/doc"), add [[Category:Robotics templates]] to the <includeonly> section at the bottom of that page.

  4. Frame problem - Wikipedia

    en.wikipedia.org/wiki/Frame_problem

    In artificial intelligence, with implications for cognitive science, the frame problem describes an issue with using first-order logic to express facts about a robot in the world. Representing the state of a robot with traditional first-order logic requires the use of many axioms that simply imply that things in the environment do not change ...

  5. Template:Cognitive - Wikipedia

    en.wikipedia.org/wiki/Template:Cognitive

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more

  6. Neurorobotics - Wikipedia

    en.wikipedia.org/wiki/Neurorobotics

    Neurorobotics is the combined study of neuroscience, robotics, and artificial intelligence.It is the science and technology of embodied autonomous neural systems. Neural systems include brain-inspired algorithms (e.g. connectionist networks), computational models of biological neural networks (e.g. artificial spiking neural networks, large-scale simulations of neural microcircuits) and actual ...

  7. Robot learning - Wikipedia

    en.wikipedia.org/wiki/Robot_learning

    The embodiment of the robot, situated in a physical embedding, provides at the same time specific difficulties (e.g. high-dimensionality, real time constraints for collecting data and learning) and opportunities for guiding the learning process (e.g. sensorimotor synergies, motor primitives).