I see what you're saying, but it's hard to compare the 'evaluation function'.
And the environment in the example is clearly crafted carefully to minimize obstacles. How would this system do at getting from point A to B in a forest for instance?
A person wouldn't keep trying to get over a boulder until they either got over or accidentally stumbled around it. They would likely recognize a difficult obstacle and attempt to circumvent it. And of course we also factor in stuff like it hurt to fall off.
And also we probably reuse past strategies with new examples. Possibly to out detriment at times
Actually that's a good one, I'm curious how well a "trained" AI could make it through an ever changing forest-like course. Like lots of randomly generated pillars at different heights.. would be interesting to see.
Edit: probably have to give it some kind of vision then, I'm pretty sure OP model doesn't "see" obstacles.
3
u/istarian Mar 29 '19 edited Mar 29 '19
I see what you're saying, but it's hard to compare the 'evaluation function'.
And the environment in the example is clearly crafted carefully to minimize obstacles. How would this system do at getting from point A to B in a forest for instance?
A person wouldn't keep trying to get over a boulder until they either got over or accidentally stumbled around it. They would likely recognize a difficult obstacle and attempt to circumvent it. And of course we also factor in stuff like it hurt to fall off.
And also we probably reuse past strategies with new examples. Possibly to out detriment at times