9 citations · 12 across the 5 of their papers we have counts for
5 papers
Prescriptive Process Monitoring Under Resource Constraints: A Reinforcement Learning Approach
Mahmoud Shoush, Marlon Dumas
Prescriptive process monitoring methods seek to optimize the performance of business processes by triggering interventions at runtime, thereby increasing the probability of positiv…
Learning When to Treat Business Processes: Prescriptive Process Monitoring with Causal Inference and Reinforcement Learning
Zahra Dasht Bozorgi, Marlon Dumas, Marcello La Rosa +3
Increasing the success rate of a process, i.e. the percentage of cases that end in a positive outcome, is a recurrent process improvement goal. At runtime, there are often certain…
Intervening With Confidence: Conformal Prescriptive Monitoring of Business Processes
Mahmoud Shoush, Marlon Dumas
Prescriptive process monitoring methods seek to improve the performance of a process by selectively triggering interventions at runtime (e.g., offering a discount to a customer) to…
When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraints
Mahmoud Shoush, Marlon Dumas
Prescriptive process monitoring approaches leverage historical data to prescribe runtime interventions that will likely prevent negative case outcomes or improve a process's perfor…
Prescriptive Process Monitoring Under Resource Constraints: A Causal Inference Approach
Mahmoud Shoush, Marlon Dumas
Prescriptive process monitoring is a family of techniques to optimize the performance of a business process by triggering interventions at runtime. Existing prescriptive process mo…