Population-Based Training (PBT) for RL.
hardAnswer
- Jaderberg et al. 2017: run N agents in parallel with different hyperparameters.
- Periodically: worst agents copy weights from top-N + perturb hyperparameters.
- Simultaneously trains agents AND does hyperparameter optimization — no manual sweep.
- Standard in complex RL (DeepMind's Capture-the-Flag, AlphaStar).
- Modern alternative: Bayesian optimization + parallel runs.
Check yourself — multiple choice
- Same as grid search
- N parallel agents with different hyperparameters; periodically bottom agents copy top weights + perturb hyperparams; simultaneous training + HPO; used in AlphaStar / CTF
- Random
- Not real
PBT: parallel training + weight-copy + HPO; AlphaStar / CTF standard.
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Practise Reinforcement Learning
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