random-subset-sum-frontier-cs-algorithmic-64

Random Subset Sum

Choose a subset whose sum is as close as possible to a target.

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

Random Subset Sum

Choose a subset whose sum is as close as possible to a target.

Solution Interface

Submit a zip_project solution. The run command is executed once per case, reads the case from standard input, and writes the answer to standard output. The trusted separated evaluator runs the migrated Frontier-CS Testlib checker against the submitted output and the case's evaluator-only answer or scoring metadata.

Scoring

The leaderboard score is the average checker ratio scaled to 0..100 across official cases. Invalid outputs receive zero for the affected case. The public validation case is intentionally tiny and deterministic; official scoring uses the source-derived Frontier-CS cases packaged as private benchmark data.

Original Statement

Given (1 <= n <= 1e2) and (B = 1e15), n integers a_1 … a_n (0 <= a_i <= B) drawn from either (normal, uniform, pareto, exponential) distributions, find a subset of a_1..a_n that sums as close as possible to T=x_i*a_i, x_i drawn from Bernoulli (1/2).

Score = 100 * (15 - log(error + 1)) / 15

25% of the test cases will be from U(0, B) 25% of the test cases will be from N(B/2, B/6) 25% of the test cases will be from Exp(B/2) 25% of the test cases will be from TruncatedPareto(m=B/3, alpha=2, max=B)

Input: n T A_1 a_2 a_3 a_4 .. a_n

Output: Print a binary string of length n, denoting the subset selection.

Sample input: 3 4 1 2 3

Sample output: 101

Configuration

Manifestagentics.solution.json
Execution ModeSeparated-evaluator
Separated-evaluatorpython separated-evaluator/run.py
EligibilityOpen
Rank MetricScore

Metrics

Scorescore · higher is better
Public
Accepted Casesaccepted_cases · higher is better · cases
Public
Average Ratioaverage_ratio · higher is better
Public
Unbounded Scoreunbounded_score · higher is better
Public

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