A characterization of strategy-proof probabilistic assignment rules
Sai Praneeth Donthu, Souvik Roy, Soumyarup Sadhukhan, Gogulapati Sreedurga

TL;DR
This paper characterizes the unique probabilistic assignment rule satisfying efficiency, individual rationality, and a weakened incentive compatibility condition, extending classical deterministic results to probabilistic settings and restricted domains.
Contribution
It introduces SD-top-strategy-proofness and characterizes the TTC rule as unique under this condition on FPT and FTT domains, extending deterministic results to probabilistic assignments.
Findings
TTC rule is unique on FPT domain satisfying SD-Pareto efficiency and SD-top-strategy-proofness.
Characterization extends to FTT domain with SD-pair efficiency.
Results generalize deterministic characterizations to probabilistic and restricted domain settings.
Abstract
We study the classical probabilistic assignment problem, where finitely many indivisible objects are to be probabilistically or proportionally assigned among an equal number of agents. Each agent has an initial deterministic endowment and a strict preference over the objects. While the deterministic version of this problem is well understood, most notably through the characterization of the Top Trading Cycles (TTC) rule by Ma (1994), much less is known in the probabilistic setting. Motivated by practical considerations, we introduce a weakened incentive requirement, namely SD-top-strategy-proofness, which precludes only those manipulations that increase the probability of an agent's top-ranked object. Our first main result shows that, on any free pair at the top (FPT) domain (Sen, 2011), the TTC rule is the unique probabilistic assignment rule satisfying SD-Pareto efficiency,…
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Taxonomy
TopicsGame Theory and Voting Systems · Auction Theory and Applications · Constraint Satisfaction and Optimization
