4 ms·
Given the perfect play reported elsewhere, this suggests that the holes are just tall enough to accomodate a single flap, so the network essentially just has to
by shmageggy 10y ago
Given the perfect play reported elsewhere, this suggests that the holes are just tall enough to accomodate a single flap, so the network essentially just has to learn the less-than function and then tune the threshold.
edit: With sigmoid or hard-threshold activation, this function is really simple to implement. If we want to flap iff bird is lower than pipe, we can do that with no hidden layers and a weight vector of [1 -1]. I'd be curious to see someone fork and implement this.
- hanoz 10y ago> Given the perfect play reported elsewhere, this suggests that the holes are just tall enough to accomodate a single flap, so the network essentially just has to learn the less-than function and then tune the threshold. Yes, slightly disappointingly the neural network can be replaced by the line: if((this.birds[i].y - 70) / this.height > nextHoll) this.birds[i].flap();