Re:Deep Reinforcement Learning: Pong from Pixels
by almostarockstar on Wednesday June 01, 2016 @06:09AM
(#11813265)
Notice how the output (or the network) is stochastic, not a solid value. You could certainly tweak the output sampling function to reduce jitter.
Further training may also reduce this, but technically, since the jitter is not causing any reduction in the reward, it might not. The best approach would likely be to alter the reward system to discourage jittery play...but again, there is no point because it does not reduce fitness.
I suppose where this is important is in robotics where jittery movement might actually be dangerous, or wear down hardware. In that case, you could certainly use an output smoothing function and tweak the reward.
Further training may also reduce this, but technically, since the jitter is not causing any reduction in the reward, it might not. The best approach would likely be to alter the reward system to discourage jittery play...but again, there is no point because it does not reduce fitness.
I suppose where this is important is in robotics where jittery movement might actually be dangerous, or wear down hardware. In that case, you could certainly use an output smoothing function and tweak the reward.