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Session: Workshop - Learning Classifier Systems (LCS) Title: Technology Extraction for Future Generations from Process Time Series Data Reflecting Expert Operator Skills     Authors: Setsuya Kurahashi Takao Terano     Abstract: This paper proposes a novel method to develop a process response model from continuous time-series data. The method consists of the following phases: (1) Reciprocal correlation analysis; (2) Process response model; (3) Extraction of control rules; (4) Extraction of a workflow. The main contribution of the research is to establish a method to mine a set of meaningful control rules from Learning Classifier System using the Minimum Description Length criteria. The proposed method has been applied to an actual process of a biochemical plant and has shown the validity and the effectiveness.