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Multi-objective reinforcement learning (MORL) approaches have emerged to tackle many real-world problems with multiple conflicting objectives by maximizing a joint objective function weighted by a preference vector.
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Addressing function approximation error in actor-critic methods
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A practical guide to multi-objective reinforcement learning and planning
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