AI RESEARCH

Adaptive Multi-Round Allocation with Stochastic Arrivals

arXiv CS.AI

ArXi:2605.12111v1 Announce Type: new We study a sequential resource allocation problem motivated by adaptive network recruitment, in which a limited budget of identical resources must be allocated over multiple rounds to individuals with stochastic referral capacity. Successful referrals endogenously generate future decision opportunities while allocating additional resources to an individual exhibits diminishing returns. We first show that the single-round allocation problem admits an exact greedy solution based on marginal survival probabilities.