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In participatory budgeting we are given a set of projects---each with a cost, an available budget, and a set of voters who in some form express their preferences over the projects. The goal is to select---based on voter preferences---a…
Self-interested behavior in sharing economies often leads to inefficient aggregate outcomes compared to a centrally coordinated allocation, ultimately harming users. Yet, centralized coordination removes individual decision power. This…
Artificial intelligence (AI) governance is the body of standards and practices used to ensure that AI systems are deployed responsibly. Current AI governance approaches consist mainly of manual review and documentation processes. While such…
This paper proposes a strategic model of pollution control. A firm, representative of the productive sector of a country, aims at maximizing its profits by expanding its production. Assuming that the output of production is proportional to…
In a single-parameter mechanism design problem, a provider is looking to sell a service to a group of potential buyers. Each buyer $i$ has a private value $v_i$ for receiving the service and a feasibility constraint restricts which sets of…
We introduce draft auctions, which is a sequential auction format where at each iteration players bid for the right to buy items at a fixed price. We show that draft auctions offer an exponential improvement in social welfare at equilibrium…
This paper considers the problem of steady-state real-time optimization (RTO) of interconnected systems with a common constraint that couples several units, for example, a shared resource. Such problems are often studied under the context…
In traditional access control policies, every access granted and administrative account introduces an additional vulnerability, as a corruption of a high-privilege user can compromise several sensitive files. Privocracy is an access control…
As the use of algorithmic systems in high-stakes decision-making increases, the ability to contest algorithmic decisions is being recognised as an important safeguard for individuals. Yet, there is little guidance on what…
In online revenue systems, e.g. an advertising system, budget pacing plays a critical role in ensuring that the spend aligns with desired financial objectives. Pacing systems dynamically control the velocity of spending to balance auction…
Current large language model agent frameworks prioritize autonomy but lack the governability mechanisms required for enterprise deployment. High-risk write operations proceed without independent review, complex tasks lack acceptance…
The need for control strategies that can address dynamic system uncertainty is becoming increasingly important. In this work, we propose a Model Predictive Control by quantifying the risk of failure in our system model. The proposed control…
In today's economy, selling a new zero-marginal cost product is a real challenge, as it is difficult to determine a product's "correct" sales price based on its profit and dissemination. As an example, think of the price of a new app or…
Revenue-optimal auction design is a challenging problem with significant theoretical and practical implications. Sequential auction mechanisms, known for their simplicity and strong strategyproofness guarantees, are often limited by…
Sealed-bid auctions play a crucial role in blockchain ecosystems. Previous works introduced viable blockchain sealed-bid auction protocols, leveraging timed commitments for bid encryption. However, a crucial challenge remains unresolved in…
This note is addressed to giving a short introduction to control theory of stochastic systems, governed by stochastic differential equations in both finite and infinite dimensions. We will mainly explain the new phenomenon and difficulties…
We consider the problem of steering a multi-agent system to multi-consensus, namely a regime where groups of agents agree on a given value which may be different from group to group. We first address the problem by using distributed…
This paper presents an algorithm to apply nonlinear control design approaches in the case of stochastic systems with partial state observation. Deterministic nonlinear control approaches are formulated under the assumption of full state…
Control of a dynamical system without the knowledge of dynamics is an important and challenging task. Modern machine learning approaches, such as deep neural networks (DNNs), allow for the estimation of a dynamics model from control inputs…
A smart grid connects wind or solar or storage farms, fossil fuel plants, industrialor commercial loads, or load serving entities, modeled as stochastic dynamical systems. In each time period, they consume or supply electrical energy, with…