JaydenTeoh/MORL-Generalization
Benchmark for evaluating the generalization capabilities of Multi-Objective Reinforcement Learning (MORL) algorithms.
This project helps researchers and developers assess how well Multi-Objective Reinforcement Learning (MORL) algorithms can adapt and perform in new, unseen environments. It takes in various MORL algorithms and predefined multi-objective environments, then outputs performance metrics and evaluation data. The primary users are researchers and practitioners working on advanced AI and reinforcement learning applications who need to validate the robustness of their algorithms.
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Use this if you are developing or studying multi-objective reinforcement learning algorithms and need a standardized way to test their generalization capabilities across different scenarios.
Not ideal if you are looking for a plug-and-play MORL solution for a specific real-world problem, as this is primarily an evaluation benchmark.
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Jun 06, 2025
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