SearcharxivSearch

arXiv subjects

Emile Martinez

Publications and source records attributed to Emile Martinez.

2 recordsLinked to original sources

Prophet Inequalities with Delayed and Uncertain Acceptance

We introduce the prophet inequality with delayed and uncertain acceptance, a variant of the classical prophet inequality in which a decision-maker sequentially evaluates options whose acceptance is uncertain and whose outcome is revealed only after a fixed delay. That is, at each time step, the decision-maker observes the realized value of the arriving option and must irrevocably decide whether to attempt to select it or to continue searching. If an option is attempted to be selected, the process is suspended for a fixed delay $d$, during which no other options can be considered. Once the delay expires, the selection succeeds with a known probability. If successful, the decision-maker receives the realized value and the process terminates; otherwise, the search resumes. In addition to the online decision-maker, we consider two stronger benchmarks: the value-aware decision-maker, who knows all value realizations in advance but not the acceptance outcomes, and the prophet, who knows both the values and the acceptance realizations. We characterize the competitive ratios between the two decision-makers and the prophet, showing that each is lower bounded by $1/(d+2)$, and we construct instances demonstrating that these bounds are tight for two of the comparisons. In the extreme case of no delay ($d=0$), where our result recovers the classical $1/2$-competitive guarantee, we establish the tightness of the remaining competitive ratio and identify sufficient conditions under which the value-aware decision-maker can beat the $1/2$ barrier against the prophet. In particular, we show that this occurs whenever all acceptance probabilities are strictly positive, by reducing the problem to a classical prophet inequality instance over appropriately scaled Bernoulli random variables.

cs.GT

Stability in Online Assignment Games

The assignment game models a housing market where buyers and sellers are matched, and transaction prices are set so that the resulting allocation is stable. Shapley and Shubik showed that every stable allocation is necessarily built on a maximum social welfare matching. In practice, however, stable allocations are rarely attainable, as matchings are often sub-optimal, particularly in online settings where eagents arrive sequentially to the market. In this paper, we introduce and compare two complementary measures of instability for allocations with sub-optimal matchings, establish their connections to the optimality ratio of the underlying matching, and use this framework to study the stability performances of randomized algorithms in online assignment games.

cs.GT