AI Snips
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RL Often Lacks Explicit Causality
- Reinforcement learning appears tied to experiments but often omits explicit causal modeling.
- This omission raises questions about why RL succeeds without formal causality handling.
Model Causality, Don’t Rely On Deep Nets
- Do not assume deep networks automatically solve causal reasoning by magic.
- Treat causal structure explicitly rather than relying on implicit representation inside networks.
Use Simple Models To Reveal Failure Modes
- Use toy models to reveal failure modes and inspect learned policies exhaustively.
- Enumerate states when possible to interpret networks and find causal errors early.