Title: Competitive Bundle Trading

Abstract: Allocating a set of resources to an online sequence of customers is a fundamental problem in online algorithms with an extensive history. However, the natural extension where the algorithm is also allowed to purchase inventory from suppliers, who also arrive online, is essentially unexplored. We study this general trading problem under the objective of profit maximization, which is the difference between revenue from sales and cost of purchases. Maximizing the difference between two competing quantities is significantly more challenging than the sell-only case.

We show a logarithmic competitive ratio relative to the optimal offline solution. Our algorithm is an exponential-weight–update dynamic pricing scheme, and our analysis dual-fits the algorithm’s profit with respect to a linear programming relaxation that upper bounds the optimal offline profit; we also prove (nearly) matching lower bounds. Finally, we extend our results by designing an incentive-compatible mechanism for the setting in which customers are strategic and may misreport their true valuations.

Joint work with Niv Buchbinder, Roie Levin and Or Vardi

Title: Sequential Cursed Equilibrium

Abstract: We propose an extensive-form solution concept, with players that neglect information from hypothetical events, but make inferences from observed events. Our concept modifies cursed equilibrium (Eyster and Rabin, 2005), and allows that players can be 'cursed about' endogenous information.

joint with Shengwu Li.

Title: The Competition Complexity of Dynamic Pricing

Abstract:  One of the most fundamental questions in mechanism design is the tradeoff between simplicity and optimality. A canonical example of this tradeoff is competition complexity in auctions, which quantifies how many additional bidders are needed for a simple mechanism to (approximately) match the revenue of the optimal mechanism.

In this talk, we analyze the competition complexity of dynamic pricing in the setting of selling a single item. We establish tight asymptotic guarantees for various scenarios, including when bidder values are i.i.d., independent, or correlated. Our results characterize the performance of different classes of dynamic pricing algorithms and provide insights into their effectiveness under varying market conditions.

Title: 

From multi-allocations to allocations, with subadditive valuations

Abstract:

  We consider the problem of fair allocation of $m$ indivisible items to $n$ agents with monotone subadditive valuations. For integer $d \ge 2$, a $d$-multi-allocation is an allocation in which each item is allocated to at most $d$ different agents. We show that $d$-multi-allocations can be transformed into allocations, while not losing much more than a factor of $d$ in the value that each agent receives. 

  One consequence of this result is that for allocation instances with equal entitlements and subadditive valuations, if $\rho$-MMS $d$-multi-allocations exist, then so do $\frac{\rho}{4d}$-MMS allocations. Combined with recent results of Seddighin and Seddighin [EC 2025], this implies the existence of $\Omega(\frac{1}{\log\log n})$-MMS allocations

Title: Compromise Design

Abstract: Two parties with (typically) conflicting interests must choose an outcome. Society values moderate outcomes, those that serve as a compromise between the two parties. We provide a parametric set of two-step mechanisms that yield such compromise in equilibrium. In the limit case the outcome corresponds to the Nash bargaining solution.

The mechanism can be easily extended to any number of agents, while maintaining the same two steps and its theoretical properties. This work was inspired by the public discourse in Israel regarding the nomination procedure supreme court Magistrates.