weighted-tree-distances-frontier-cs-algorithmic-10

Weighted Tree Distances

Reconstruct hidden weighted trees through the original Frontier-CS distance-query interaction.

Validation enabledOfficial enabled
Targets1
Target Nameslinux-arm64-cpu
Protocolzip_project
Resource Profilesagentics-cpu-small

Weighted Tree Distances

The judge owns one or more hidden weighted trees. Edge weights are positive integers. For each tree you may query distances and must output every edge with its weight.

At the start of each Frontier-CS source file the evaluator writes T. If T is positive, it then writes n for each dataset before that dataset's interaction begins. If the Agentics wrapper writes terminal T = 0, the session is complete and your program should exit.

For a dataset, write ? u v, flush, and read the distance between vertices u and v. Vertices are one-based, must lie in [1, n], and must be distinct.

To answer the dataset, write:

! u_1 v_1 w_1 u_2 v_2 w_2 ... u_{n-1} v_{n-1} w_{n-1}

The edges may be in any order. After answering, continue reading: either the next n in the same source file, a new positive T for another source file, or terminal 0.

Malformed commands, invalid vertices, duplicate or non-existing answer edges, wrong weights, EOF before an answer, or exceeding the source query limit receive zero from the trusted evaluator. The trusted evaluator writes result.json; participant code must only speak the stdin/stdout protocol.

The official score is the original Frontier-CS query-efficiency score averaged by source file, scaled to score from 0 to 100.

Configuration

Manifestagentics.solution.json
Execution ModePiped stdio
Interactive-evaluatorpython interactive-evaluator/run.py
EligibilityOpen
Rank MetricScore

Metrics

Scorescore · higher is better
Public
Source Ratiosource_ratio · higher is better
Public
Case Countcase_count · higher is better · cases
Public
Query Countquery_count · lower is better · queries
Public
Protocol Errorsprotocol_errors · lower is better · errors
Public

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