Questions tagged [reward]

A reward is the network feedback in a reinforcement-learning setting. Reward functions describe how an agent is awarded for its actions in a given state.

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Frozen baseline for policy gradient rewards

I have a continuous reinforcement learning problem for which I use policy gradients and I use a baseline to decrease the variance of the gradients. The baseline that I used is the moving average of ...
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What can I infer if large negative penalties are not increasing?

I am running a Deep RL algorithm. I defined a custom reward function. I run the algorithm for at least 500 epochs. For each epoch, I am printing the total reward received by the actor-network. It is ...
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Q-learning episode and relation to convergence in MY scenario?

I used Q-learning for routing. I have used the Bellman equation. I have certain other technical aspects in the code that add some novelty. But I have mixed doubts regarding episode and corresponding ...
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Reinforcement learning policy gradient derivation

I was reading a document about Reinforcement Learning policy gradient http://web.stanford.edu/class/cs234/CS234Win2019/slides/lnotes8.pdf when I encountered this expression $ \nabla_{\theta} \mathbb{...
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How to write a reward function that optimizes for profit and revenue?

So I want to write a reward function for a reinforcement learning model which picks products to display to a customer. Each product has a profit margin %. Higher price products will have a higher ...
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What is a good reward function when objective is to minimize the average along with the variance?

I am trying to formulate a problem where we are trying to minimize the average resource allocated to different users. Due to some inherent properties of the environment, some users can be easily ...