If you have the model of something, its as good as knowledge, implicit* models are easier to think about, and take lots of sampling. For example a physics engine and an accurate geometry of its surroundings and you can get the truths of the environment, sans geometry you cant model. (like gas for example.)
If the robot could use this physics+geometry in a more optimized explicit fashion, then maybe alot less computational resources are required. Any thoughts? * I mean implicit through multisampling. ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T8fe5317c3cebf70b-M1e16e89d3782fc191facd915 Delivery options: https://agi.topicbox.com/groups/agi/subscription
