SOURCE-LINKED INTELLIGENCE
Learning to Allocate Incentives for Incentivized Advertising via Offline Model-Based Reinforcement Learning
Complete your ad view and grab a 5-cent bonus! In incentivized advertising, a platform promises users a bonus before observing downstream ad revenue, encouraging them to click and complete ads. It must balance the incentive promised in advance against the revenue realized afterward: insufficient incentives forfeit monetization opportunities, whereas excessive incentives reduce net profit. Because current incentives may also shape user expectations and future engagement, incentive allocation is a sequential decision problem with delayed revenue, cost sensitivity, and carryover effects. Existing
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-28T08:35:41.000Z
First collected: 2026-09-21T08:21:55.975Z. This is not the publication date.