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Found 2 papers, 1 papers with code
Tiered Reward Functions: Specifying and Fast Learning of Desired Behavior
Reinforcement-learning agents seek to maximize a reward signal through environmental interactions.
Designing Rewards for Fast Learning
To solve this optimization problem, we propose a linear-programming based algorithm that efficiently finds a reward function that maximizes action gap and minimizes subjective discount.
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