On a Successful Application of Multi-Agent Reinforcement Learning to Operations Research Benchmarks

@article{Gabel2007OnAS,
  title={On a Successful Application of Multi-Agent Reinforcement Learning to Operations Research Benchmarks},
  author={Thomas Gabel and Martin Riedmiller},
  journal={2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning},
  year={2007},
  pages={68-75}
}
In this paper, we suggest and analyze the use of approximate reinforcement learning techniques for a new category of challenging benchmark problems from the field of operations research. We demonstrate that interpreting and solving the task of job-shop scheduling as a multi-agent learning problem is beneficial for obtaining near-optimal solutions and can very well compete with alternative solution approaches. The evaluation of our algorithms focuses on numerous established operations research… CONTINUE READING

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