Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
On profit-maximizing envy-free pricing
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Approximation algorithms and online mechanisms for item pricing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Algorithmic pricing via virtual valuations
Proceedings of the 8th ACM conference on Electronic commerce
Item pricing for revenue maximization
Proceedings of the 9th ACM conference on Electronic commerce
Multi-parameter mechanism design and sequential posted pricing
Proceedings of the forty-second ACM symposium on Theory of computing
Pricing randomized allocations
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Multi-parameter mechanism design and sequential posted pricing
Proceedings of the forty-second ACM symposium on Theory of computing
Prior-independent multi-parameter mechanism design
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
Budget feasible mechanism design: from prior-free to bayesian
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
An algorithmic characterization of multi-dimensional mechanisms
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Symmetries and optimal multi-dimensional mechanism design
Proceedings of the 13th ACM Conference on Electronic Commerce
Proceedings of the 13th ACM Conference on Electronic Commerce
On revenue maximization for agents with costly information acquisition: extended abstract
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
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We investigate the power of randomness in the context of a fundamental Bayesian optimal mechanism design problem - a single seller aims to maximize expected revenue by allocating multiple kinds of resources to "unit-demand" agents with preferences drawn from a known distribution. When the agents' preferences are single-dimensional Myerson's seminal work [14] shows that randomness offers no benefit - the optimal mechanism is always deterministic. In the multi-dimensional case, where each agent's preferences are given by different values for each of the available services, Briest et al.[6] recently showed that the gap between the expected revenue obtained by an optimal randomized mechanism and an optimal deterministic mechanism can be unbounded even when a single agent is offered only 4 services. However, this large gap is attained through unnatural instances where values of the agent for different services are correlated in a specific way. We show that when the agent's values involve no correlation or a specific kind of positive correlation, the benefit of randomness is only a small constant factor (4 and 8 respectively). Our model of positively correlated values (that we call the common base value model) is a natural model for unit-demand agents and items that are substitutes. Our results extend to multiple agent settings as well.