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Found 2 papers, 1 papers with code
Safety-Constrained Policy Transfer with Successor Features
In this work, we focus on the problem of safe policy transfer in reinforcement learning: we seek to leverage existing policies when learning a new task with specified constraints.
SCALES: From Fairness Principles to Constrained Decision-Making
This paper proposes SCALES, a general framework that translates well-established fairness principles into a common representation based on the Constraint Markov Decision Process (CMDP).
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