Questions tagged [reward-design]
For questions about designing (or defining) reward functions e.g. for reinforcement learning problems.
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How should I handle invalid actions (when using REINFORCE)?
I want to create an AI which can play five-in-a-row/Gomoku. I want to use reinforcement learning for this.
I use the policy gradient method, namely REINFORCE, with baseline. For the value and policy ...
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How do we define the reward function for an environment?
How do you actually decide what reward value to give for each action in a given state for an environment?
Is this purely experimental and down to the programmer of the environment? So, is it a ...
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Can reinforcement learning be used for tasks where only one final reward is received?
Is reinforcement learning problem adaptable to the setting when there is only one - final - reward. I am aware of problems with sparse and delayed rewards, but what about only one reward and a quite ...
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What are some best practices when trying to design a reward function?
Generally speaking, is there a best-practice procedure to follow when trying to define a reward function for a reinforcement-learning agent? What common pitfalls are there when defining the reward ...
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How should I define the reward function to solve the Wumpus game with deep Q-learning?
I'm writing a DQN agent for the Wumpus game.
Is the reward function to train the Q-networks (target network and policy) the same as the score of the game, i.e. +1000 for picking up gold, -1000 for ...
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Counterexamples to the reward hypothesis
On Sutton and Barto's RL book, the reward hypothesis is stated as
that all of what we mean by goals and purposes can be well thought of as the maximization of the expected value of the cumulative ...
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How can I implement the reward function for an 8-DOF robot arm with TRPO?
I need to get an 8-DOF (degrees of freedom) robot arm to move a specified point. I need to implement the TRPO RL code using OpenAI gym. I already have the gazebo environment. But I am unsure of how to ...
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Suitable reward function for trading buy and sell orders
I am working to build a deep reinforcement learning agent which can place orders (i.e. limit buy and limit sell orders). The actions are ...
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Is a reward given at every step or only given when the RL agent fails or succeeds?
In reinforcement learning, an agent can receive a positive reward for correct actions and a negative reward for wrong actions, but does the agent also receive rewards for every other step/action?
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Reinforcement Learning algorithm with rewards dependent both on previous action and current action
Problem description:
Suppose we have an environment, where a reward at time step $t$ is dependent not only on the current action, but also on previous action in the following way:
if current action ==...
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