Equal-Budget Monte Carlo Tree Search versus Randomized-Restart List Scheduling for DAG Workflows: A Controlled Equal-Budget Computational Study

Author1, Author2, Author3, Author4, Author5

schedulingDAG workflowsMonte Carlo Tree Searchlist scheduling

2610.12542

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70%

8h ago

Abstract

This study compares Monte Carlo Tree Search (MCTS) and randomized-restart list scheduling for DAG workflows under a controlled budget, revealing that MCTS performs worse than simpler methods.

Reality Card

Core Claim

MCTS is 2.88% worse than randomized-restart list scheduling under equal budget conditions, indicating that simpler methods can outperform MCTS in certain scenarios.

Method / Result

At a budget of 2048 evaluated schedules, MCTS is 2.88% worse than the randomized-restart method.

Limitations

Results are confined to a controlled synthetic domain with limited task and processor configurations, raising concerns about generalizability.

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