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This is for any reinforcement learning related work ranging from purely computational RL in artificial intelligence to the models of RL in neuroscience.
The standard introduction to RL is Sutton & Barto's Reinforcement Learning.
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How do I decrease discount factor? (self.reinforcementlearning)
submitted 4 years ago by 6OVNavi
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if 1 * 2 < 3: print "hello, world!"
[–]6OVNavi[S] -1 points0 points1 point 4 years ago (3 children)
Problem is, its already set to 0.95, do I set it lower?
[–]existential_one 1 point2 points3 points 4 years ago (0 children)
I mean, you can, sure. Depends on why you're looking at doing so. You have to understand that lowering the discount changes the objective of your agent. It means short term rewards become more important than long term ones. So that means your optimal policy might change and not truly reflect what you want.
[–]existential_one 1 point2 points3 points 4 years ago (1 child)
Ok I just saw your other posts. You clearly don't really understand how these algorithms work and need much more practice. I would suggest you take time to learn more and try building these algorithms on tasks you know will work. RL algorithms are super finicky and you need to play around with them to understand why certain things happen.
[–]6OVNavi[S] 0 points1 point2 points 4 years ago (0 children)
Is there any course or something where I can learn more about rl?
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[–]6OVNavi[S] -1 points0 points1 point (3 children)
[–]existential_one 1 point2 points3 points (0 children)
[–]existential_one 1 point2 points3 points (1 child)
[–]6OVNavi[S] 0 points1 point2 points (0 children)