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Found 2 papers, 1 papers with code
Nonlinear Multi-objective Reinforcement Learning with Provable Guarantees
We first state a distinct reward-aware version of value iteration that calculates a non-stationary policy that is approximately optimal for a given model of the environment.
Welfare and Fairness in Multi-objective Reinforcement Learning
We study fair multi-objective reinforcement learning in which an agent must learn a policy that simultaneously achieves high reward on multiple dimensions of a vector-valued reward.
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