A General Framework for Budgeted Threshold Incentives on Request
Quick summary
arXiv:2609.29724v1 Announce Type: new Abstract: On-demand delivery platforms pay riders through incentive activities whose tiers are set from recent completions of riders with a similar history. Operators request such plans for changing periods, rider populations, payment rules and budgets, often for holidays or bad weather, where randomized trials are scarce and take months to collect. We present a request-driven framework that composes four stages (conditional prediction, population reduction, trajectory integration and budget allocation) through seven replaceable modules that exchange condi
Key takeaways
- arXiv:2609.29724v1 Announce Type: new Abstract: On-demand delivery platforms pay riders through incentive activities whose tiers are set from recent completions of riders with a similar history.
- Operators request such plans for changing periods, rider populations, payment rules and budgets, often for holidays or bad weather, where randomized trials are scarce and take months to collect.
- We present a request-driven framework that composes four stages (conditional prediction, population reduction, trajectory integration and budget allocation) through seven replaceable modules that exchange condi
Why it matters
“A General Framework for Budgeted Threshold Incentives on Request” is a product decision that may change how people work with AI. Its value depends on task completion, correction effort and data handling—not simply the presence of a new feature.
Member comments