arXiv AI June 15, 2026 By Stefano Branchi, Andrei Buliga, Chiara Di Francescomarino, Chiara Ghidini, Riccardo Graziosi, Francesca Meneghello, Massimiliano Ronzani

Learning optimal policies from event logs through reinforcement learning: a comparison of deep and MDP-based approaches

Read the original on arXiv AI →

arXiv:2303. 09209v2 Announce Type: replace Abstract: Prescriptive Process Monitoring is an emerging area within Process Mining that focuses on recommending actions to optimize business outcomes.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 10

SCOPE: Sequential Causal Optimization of Process Interventions

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arXiv Machine Learning

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arXiv:2607. 28408v1 Announce Type: new Abstract: This thesis studies policy learning in interactive systems where an agent observes a context, selects an action from a very large set, and receives partial feedback.

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agents diffusion safety

arXiv AI

Jul 15

Knowledge- and Gradient-Guided Reinforcement Learning for Parametrized Action Markov Decision Processes

arXiv:2607. 12924v1 Announce Type: new Abstract: In this paper, we study Reinforcement Learning in Parametrized Action Markov Decision Processes (PAMDP), where each decision consists of a symbolic action and numerical parameters.

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arXiv Machine Learning

Jul 31

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arXiv AI

Jul 14

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arXiv Machine Learning

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SCOPE: Sequential Causal Optimization of Process Interventions

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