Interaction Data and Passive Observation › Key Parameters
Michael BrenndoerferJuly 3, 20261 min read
World Models HandbookAll chapters Part 6 of 12Learning World Models at Scale
Interaction Data and Passive Observation › Key ParametersOne section · Sections in this chapter9 / 10 ↓
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The key parameters in the worked example are:
- A_TRUE: State persistence coefficient (0.9). Determines how much current state carries forward.
- B_TRUE: Linear action coefficient (0.5). Determines the direct effect of the action.
- CURVATURE_TRUE: Positive-action curvature coefficient (0.35). Adds nonlinearity for positive actions.
- NOISE_STD: Process noise standard deviation (0.05). Controls stochasticity of transitions.
- n_episodes: Number of trajectories collected (200). More episodes increase coverage but cost more interaction.
- horizon: Steps per episode (20). It controls the number of correlated transitions collected per episode; the example evaluates one-step error rather than rollout compounding.
- behavior_biased: Behavior policy that determines the collected state-action distribution. The held-out target actions are sampled uniformly and paired with resampled behavior states.