Planning and Scheduling Business Processes under Control-Flow Uncertainty
arXiv cs.AIen
arXiv:2609.05578v1 Announce Type: new Abstract: Scheduling activities in business processes can improve efficiency (e.g., reduce makespan), but is challenging because the exact sequence of activities required to complete a case is often uncertain due to decisions based on data that emerges during execution. Nevertheless, probabilistic information regarding such decisions can often be estimated or derived from historical execution logs, and can help anticipate which execution paths are likely to lead to successful completion. Planning with particular execution paths affects feasibility, i.e., the probability of successful completion, and the expected number of superfluous activities that are
This is a short summary published by AI Global Wire. The full article is owned and hosted by arXiv cs.AI — open it there to read it in full.
Read the full story at arXiv cs.AI- Forskning
Related AI news
- Agents Trust Tools Too Much: Measuring Reliance on Unreliable ToolsarXiv cs.AI · September 9, 2026
- Distilling Vision-Language Models for On-Device Fire UnderstandingarXiv cs.AI · September 9, 2026
- When and What to Teach: Budget-Aware Online Adaptation for Web AgentsarXiv cs.AI · September 9, 2026
- RAPID: Reliability-Aware Pair Importance DistillationarXiv cs.AI · September 9, 2026
- Beyond "AI Helps Humans": Decision-Targeted Evaluation Design for Human-Agent Teams in the Agentic EraarXiv cs.AI · September 9, 2026
- Damage-Aware Bandit Pruning for Vision and Language TransformersarXiv cs.AI · September 9, 2026