A user on Reddit's r/MachineLearning subreddit is seeking advice on hyperparameter tuning for a comparative study of multi-agent reinforcement learning (MARL) models. They are training PPO variants on various MARL tasks and have observed that optimal hyperparameters differ across architectures and scenarios. The core question is whether to unify these hyperparameters for a fair comparison, acknowledging that this can sometimes lead to non-converging models. The user's ultimate goal is to test the robustness of these models against adversarial attacks. AI
IMPACT Clarifies best practices for ensuring methodological rigor in comparative AI research.
RANK_REASON User query about research methodology for comparative study of AI models. [lever_c_demoted from research: ic=1 ai=1.0]
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