| { |
| "id": "ml16-root", |
| "requirements": "A credible experiment comparing bandit algorithms (epsilon-greedy, UCB1, Thompson sampling, Exp3, or equivalents) under stationary and drifting synthetic regimes: algorithms are implemented with a common interface, experiments cover multiple environments with repeated seeds, and results address H1/H2/H3 directionally using cumulative regret.", |
| "judging_note": "Score on scientific substance and directional correctness of evidence, not on exact numeric thresholds. Well-motivated algorithm variants (e.g., UCB-V, linear Thompson) should be credited when they test the same scientific question.", |
| "weight": 1, |
| "sub_tasks": [ |
| { |
| "id": "ml16-code", |
| "requirements": "The bandit algorithms and synthetic environments are implemented correctly.", |
| "weight": 2, |
| "sub_tasks": [ |
| { |
| "id": "ml16-code-algos", |
| "requirements": "The submission implements multiple distinct algorithm code paths \u2014 typically including epsilon-greedy, UCB1, Thompson sampling, and/or Exp3 \u2014 with per-round action selection and update logic that are not identical wrappers.", |
| "weight": 12.5, |
| "sub_tasks": [], |
| "task_category": "Code Development", |
| "finegrained_task_category": "Method Implementation" |
| }, |
| { |
| "id": "ml16-code-envs", |
| "requirements": "The submission defines multiple synthetic bandit environments including at least one stationary and one drifting regime, with reproducible seed control and oracle best-arm rewards per round for regret computation.", |
| "weight": 6.25, |
| "sub_tasks": [], |
| "task_category": "Code Development", |
| "finegrained_task_category": "Experimental Setup" |
| }, |
| { |
| "id": "ml16-code-thompson-exp3", |
| "requirements": "If Thompson sampling and/or Exp3 are included, implementation uses sampling-based posterior decisions (Thompson) and probability-weighted action selection with importance-weighted updates (Exp3), rather than greedy mean selection.", |
| "weight": 6.25, |
| "sub_tasks": [], |
| "task_category": "Code Development", |
| "finegrained_task_category": "Method Implementation" |
| } |
| ], |
| "task_category": null, |
| "finegrained_task_category": null |
| }, |
| { |
| "id": "ml16-exec", |
| "requirements": "Execution produces regret metrics across algorithms and datasets.", |
| "weight": 2, |
| "sub_tasks": [ |
| { |
| "id": "ml16-exec-runs", |
| "requirements": "Execution runs multiple seeds per (algorithm, dataset) cell for multiple environments and logs final cumulative-regret values with mean and dispersion. Honest small-seed runs with variance reported are preferable to a single run.", |
| "weight": 16.6667, |
| "sub_tasks": [], |
| "task_category": "Code Execution", |
| "finegrained_task_category": "Evaluation, Metrics & Benchmarking" |
| }, |
| { |
| "id": "ml16-exec-artifacts", |
| "requirements": "A machine-readable results artifact is produced containing dataset-wise metrics for each implemented algorithm, including cumulative regret.", |
| "weight": 8.3333, |
| "sub_tasks": [], |
| "task_category": "Code Execution", |
| "finegrained_task_category": "Logging, Analysis & Presentation" |
| } |
| ], |
| "task_category": null, |
| "finegrained_task_category": null |
| }, |
| { |
| "id": "ml16-results", |
| "requirements": "Findings address H1/H2/H3 directionally and summarize implications.", |
| "weight": 3, |
| "sub_tasks": [ |
| { |
| "id": "ml16-result-h1", |
| "requirements": "The submission compares stationary-regime cumulative regret between epsilon-greedy and {UCB1, Thompson} and conveys whether the principled algorithms are meaningfully better \u2014 judge directionally against H1.", |
| "weight": 20.0, |
| "sub_tasks": [], |
| "task_category": "Result Analysis", |
| "finegrained_task_category": "Evaluation, Metrics & Benchmarking" |
| }, |
| { |
| "id": "ml16-result-h2", |
| "requirements": "The submission evaluates drifting-regime cumulative regret and conveys whether more exploratory algorithms (epsilon-greedy or Exp3) outperform UCB1 on most drifting datasets (H2).", |
| "weight": 10.0, |
| "sub_tasks": [], |
| "task_category": "Result Analysis", |
| "finegrained_task_category": "Evaluation, Metrics & Benchmarking" |
| }, |
| { |
| "id": "ml16-result-h3", |
| "requirements": "The submission conveys whether any single algorithm dominates across all environments or whether winners are mixed (H3), with supporting tables or summaries.", |
| "weight": 10.0, |
| "sub_tasks": [], |
| "task_category": "Result Analysis", |
| "finegrained_task_category": "Logging, Analysis & Presentation" |
| }, |
| { |
| "id": "ml16-result-writeup", |
| "requirements": "The README or writeup describes setup, reports key cumulative-regret results per environment, conveys per-hypothesis outcomes (supported / refuted / inconclusive), and notes limitations (horizon length, hyperparameter sensitivity, synthetic-only scope). No strict word-count requirement.", |
| "weight": 10.0, |
| "sub_tasks": [], |
| "task_category": "Result Analysis", |
| "finegrained_task_category": "Logging, Analysis & Presentation" |
| } |
| ], |
| "task_category": null, |
| "finegrained_task_category": null |
| } |
| ], |
| "task_category": null, |
| "finegrained_task_category": null |
| } |
|
|
