{"type":"ScholarlyArticle","title":"A Reinforcement Learning Approach to job-shop Scheduling","authors":[{"name":"Wei Zhang","slug":"wei-zhang","given":"Wei","family":"Zhang","affiliation":""},{"name":"Thomas G. Dietterich","slug":"thomas-g-dietterich","given":"Thomas G.","family":"Dietterich","affiliation":""}],"abstract":"We apply reinforcement learning methods to learn domain-specific heuristics for job shop scheduling. A repair-based scheduler starts with a critical -path schedule and incrementally repairs const ra int violations with the goal of finding a s hort conflict-free schedule. The temporal difference al gorithm TD(>..) is applied to train a neural network to learn a heuristic evaluation function over states. This evaluation function is used by a one-step lookahead search procedure to find good solutions to new scheduling problems. We evalu ate t his approach on sy nth etic problems and on problems from a NASA space shuttle payload processing tas k. The evalu ation function is trained on problems involving a small numb er of jobs and then tested on larger problems. The TD scheduler performs better t h an the best known existing algorithm for this task-Zweben 's iterative repair method based on si mul ated ann ea ling. The results suggest that reinforcement learning can provide a new method for constructing high-performance scheduling systems.","doi":null,"url":"https://ijcai.org/proceedings/1995/144","pdf":"https://ijcai.org/proceedings/1995/0144.pdf","markdown":"https://ijcai.org/proceedings/1995/144.md","bibtex":"https://ijcai.org/proceedings/1995/bibtex/144","volume":{"slug":"1995","title":"Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1995","url":"https://ijcai.org/proceedings/1995/","year":1995,"location":"Montréal, Québec, Canada","dates":"","editors":"Chris S. Mellish","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Learning","track":"Learning","number":144,"pages":{"first":1114,"last":1119},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}