The pile of problems in Robotics reminds me of the challenges faced by computer vision before modern methods were developed. To generalize the issue: humans lea

The pile of problems in Robotics reminds me of the challenges faced by computer vision before modern methods were developed. To generalize the issue: humans learn and perform vision and navigational tasks "below" the level of language. To use a vivid example, you can use language to teach a child how to hold a pencil and write, how to recognize digits, and how to do two digit addition. But there's some cognitive ability "below" the level language a child needs to be capable of in order to take the hints from language and develop the desired skills. In computer vision, we now have something like this in ConvLayers. In today's robotics we see the hyper-systematization and mathematization of natural concepts like getting an agent to recognize its own bearing. This is what I refer to as "at the level of language", and I think as long as we try to solve these individual navigation problems from mathematical first principles we'll never arrive anywhere near the performance of animal "instinct". We need a new framework that doesn't look like an enumeration of commands within an imperative program.