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candidate_idx
int64
cell_idx
int64
length
int64
nut_peg_distance
float64
nut_x
float64
nut_x_idx
int64
nut_y
float64
nut_y_idx
int64
nut_yaw
float64
nut_yaw_idx
int64
peg_x
float64
peg_x_idx
int64
peg_y
float64
peg_y_idx
int64
point_idx
int64
reward
float64
success
int64
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sim-square-broad-r00-r03-eval

Simulation evaluation evidence for Mulligan.

This bundle contains 120 locked DIVL evaluations, five training seeds per cell, including the campaign's mainline and explicitly named ablation cells. The public Policy Arena selects only mainline comparisons.

Each Parquet row is one evaluated initial state. success is binary, length is the rollout's control-step count, and point_idx joins the exact grid linked by meta/evaluations.json. Pairing requires the same grid manifest hash and training-seed protocol; do not pair unrelated grids by row number.

The evaluation index pins actor and critic artifacts, N=32 action proposals, source-result hashes, state-grid hashes, and every released Parquet file hash. It preserves original cell identifiers as provenance. Historical scalar-IQL collector rollouts remain separate from these DIVL evaluations. Evaluation videos were not recorded. Do not interpret these tables as LeRobot trajectories.

meta/mainline-evaluations.json additionally maps all 160 displayed seed results for this task (eight methods, four rounds, five seeds) to verified per-state outcomes, including actor-only and autonomous comparators. Reused R0 comparator measurements explicitly share the same data file. The recorded proposal count is preserved separately from the series label; R0 is a shared historical baseline.

The associated trajectory repositories preserve their source Apache-2.0 license declarations. The evaluation metadata and results in this bundle use Apache-2.0.

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