Timed Process Interventions: Causal Inference vs. Reinforcement Learning

Author:

Weytjens HansORCID,Verbeke WouterORCID,De Weerdt JochenORCID

Publisher

Springer Nature Switzerland

Reference20 articles.

1. Bica, I., Alaa, A.M., Jordon, J., van der Schaar, M.: Estimating counterfactual treatment outcomes over time through adversarially balanced representations. CoRR abs/2002.04083 (2020). https://arxiv.org/abs/2002.04083

2. Bozorgi, Z.D., Irene Teinemaa, I., Dumas, M., La Rosa, M., Polyvyanyy, A.: Prescriptive process monitoring based on causal effect estimation. Inf. Syst. 116, 102198 (2023). https://doi.org/10.1016/j.is.2023.102198

3. Bozorgi, Z.D., Teinemaa, I., Dumas, M., Rosa, M.L., Polyvyanyy, A.: Prescriptive process monitoring for cost-aware cycle time reduction. In: 2021 3rd International Conference on Process Mining (ICPM), pp. 96–103 (2021). https://doi.org/10.1109/ICPM53251.2021.9576853

4. Lecture Notes in Business Information Processing;S Branchi,2022

5. Bugaenko, A.A.: Application of reinforcement learning to optimize business processes in the bank. Turk. J. Comput. Math. 12, 1638–1644 (2021)

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