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Datasets:
Moon-Young-Choi
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HUTACE_Mapzen_Benchmark

Tags:
reinforcement-learning
exploration
terrain
benchmark
mapzen
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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
schema_version: int64
phase: int64
recorded_at: string
status: string
cause: string
metric_computation_affected: bool
model_or_checkpoint_affected: bool
test_spec_affected: bool
persistence_affected: bool
v1_completed_results_invalidated: int64
v1_active_jobs_canceled: int64
rerun_scope: string
fix: string
v2_runner_sha256: string
v2_bundle_sha256: string
v2_bundle_inventory_sha256: string
v1_results_retained_for_audit_but_excluded_from_analysis: bool
terrain_id: string
coverage_at_320: double
reached_0_50: bool
energy_to_0_50: double
return: double
revisit_ratio: double
fuel_used: double
decisions: double
coverage: double
distance_m: double
coverage_gain: double
energy_joules: double
coverage_auc: double
split: string
start_seed: int64
to
{'coverage': Value('float64'), 'coverage_at_320': Value('float64'), 'coverage_auc': Value('float64'), 'coverage_gain': Value('float64'), 'decisions': Value('float64'), 'distance_m': Value('float64'), 'energy_joules': Value('float64'), 'energy_to_0_50': Value('float64'), 'fuel_used': Value('float64'), 'reached_0_50': Value('bool'), 'return': Value('float64'), 'revisit_ratio': Value('float64'), 'split': Value('string'), 'start_seed': Value('int64'), 'terrain_id': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              schema_version: int64
              phase: int64
              recorded_at: string
              status: string
              cause: string
              metric_computation_affected: bool
              model_or_checkpoint_affected: bool
              test_spec_affected: bool
              persistence_affected: bool
              v1_completed_results_invalidated: int64
              v1_active_jobs_canceled: int64
              rerun_scope: string
              fix: string
              v2_runner_sha256: string
              v2_bundle_sha256: string
              v2_bundle_inventory_sha256: string
              v1_results_retained_for_audit_but_excluded_from_analysis: bool
              terrain_id: string
              coverage_at_320: double
              reached_0_50: bool
              energy_to_0_50: double
              return: double
              revisit_ratio: double
              fuel_used: double
              decisions: double
              coverage: double
              distance_m: double
              coverage_gain: double
              energy_joules: double
              coverage_auc: double
              split: string
              start_seed: int64
              to
              {'coverage': Value('float64'), 'coverage_at_320': Value('float64'), 'coverage_auc': Value('float64'), 'coverage_gain': Value('float64'), 'decisions': Value('float64'), 'distance_m': Value('float64'), 'energy_joules': Value('float64'), 'energy_to_0_50': Value('float64'), 'fuel_used': Value('float64'), 'reached_0_50': Value('bool'), 'return': Value('float64'), 'revisit_ratio': Value('float64'), 'split': Value('string'), 'start_seed': Value('int64'), 'terrain_id': Value('string')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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coverage
float64
coverage_at_320
float64
coverage_auc
float64
coverage_gain
float64
decisions
float64
distance_m
float64
energy_joules
float64
energy_to_0_50
float64
fuel_used
float64
reached_0_50
bool
return
float64
revisit_ratio
float64
split
string
start_seed
int64
terrain_id
string
0.950928
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0.928223
65
17,639.525321
1,910,710.647997
193.741847
639.333015
true
0.928223
0.01378
test
723,403,977
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0.636719
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test
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true
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test
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true
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test
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639.705896
true
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test
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true
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test
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true
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test
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true
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test
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true
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test
241,175,794
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true
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test
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mapzen-0ccc3853d8180a481aa0
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true
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test
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mapzen-0d224e32bac299b746e4
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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test
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true
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test
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End of preview.

HUTACE Mapzen benchmark results

This private repository contains the frozen configurations, raw episode rows, coverage curves, aggregation script, statistical tables, and figures for the HUTACE Mapzen experiment.

Immutable inputs

  • Terrain dataset: Moon-Young-Choi/HUTACE_Mapzen_Terrain_Benchmark
  • Test specs: 256 terrain–start pairs, fixed seed 230524
  • Learned runs: four methods × ten training seeds

Rebuild tables and figures

Install the HUTACE research package and run:

python scripts/phase13_generate_statistics.py

Directory layout

  • configs/: frozen experiment configuration.
  • raw/learned_results_v2/: 40 audited learned-policy summaries, episode rows, and coverage curves.
  • raw/heuristics/: three fair heuristics plus the diagnostic oracle.
  • analysis/: paper-ready aggregate tables and coverage–energy figure.
  • scripts/: one-command statistics generator.
  • reports/: phase gates, checksum audits, and test-incident disclosure.
  • docs/: canonical limitations and Mapzen attribution.

The repository is private during paper preparation. Public licensing must be selected explicitly before publication.
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