automl / automl/DACBench

Run fresh baselines

Open
#145 0 comments 0 reactions 0 assignees View on GitHub
enhancement
Dominant language
PDDL
Stars
39
Forks
19
PR merge metrics
No merged PRs in 30d

Description

For each benchmark, we'd want:
- static actions
- random dynamic
- tuned RL
- any known solution policies (e.g. CSA)
- optimal solution if it exists

Contributor guide

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Research direction

Start by identifying every benchmark covered by DACBench and how each benchmark is currently run. For each one, establish runs for static actions, random dynamic, tuned RL, known solution policies such as CSA, and an optimal solution where available. The work is done when fresh baseline results exist for every benchmark and the run details are recorded.

Written by the indexing model from the issue text.

Assessment

Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
35/100

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