3 ms·
I did my msc thesis in AI back then writing a dedicated simulater for a specific robot used in autonomous systems research. You find that especially when trying
by PeterStuer 7y ago
I did my msc thesis in AI back then writing a dedicated simulater for a specific robot used in autonomous systems research. You find that especially when trying to faithfully reproduce sensor signals you need to dive deep into not just the physics of e.g. infrared light, but also the specific electronic operation of the sensor itself.
But that kind of realism is not needed for all AGI research.
I also spent some years on using evolutionary algorithms to evolve control networks for simple robots. The computational resources available at the time were rather limited though. Should be more promising these days now that your commodity gaming pc can spew out in 30 minutes what back then took all the labs networked machines running each night for a few weeks.
- ivanhoe 7y agoModeling everything realistically is super hard - any interaction with the real-world is so full of the weirdest unexpected electric and mechanical issues. Who hasn't tried it first-hand can't imagine the half of ways that will almost certainly go wrong on the first try :) ... but as you've said for developing the AGI as a concept simplified worlds should work just fine.
- amatic 7y agoTrue. Simulations are always a simplification of reality and leave a lot out of the picture. On the flip side, successful robotics concepts might have more chance of being relevant to AGI.
- joe_the_user 7y agoIndeed, I don't think humans themselves model the world realistically, I think they model the world close enough but are able to adapt their prediction process for situation when their prediction don't work and/or their knowledge is inadequate. To model such a "satisficing" process, you don't need exact simulation.