Analyzing the Emergence of Semantic Agreement among Rational Agents

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In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

A plethora of real world problems consist of a number of agents that interact, learn, cooperate, coordinate, and compete with others in ever more complex environments. Examples include autonomous vehicles, robotic agents, intelligent infrastructure, IoT de ...

Can artificial agents benefit from human conventions? Human societies manage to successfully self-organize and resolve the tragedy of the commons in common-pool resources, in spite of the bleak prediction of non-cooperative game theory. On top of that, rea ...

We derive conditions under which a peer-consistency mechanism can be used to elicit truthful data from non-trusted rational agents when an aggregate statistic of the collected data affects the amount of their incentives to lie. Furthermore, we discuss the ...

Data-driven and model-driven methodologies can be regarded as competitive fields since they tackle similar problems such as prediction. However, these two fields can learn from each other to improve themselves. Indeed, data-driven methodologies have been d ...

We develop a methodology to measure the expected loss of commercial banks in a market downturn, which we call stressed expected loss (SEL). We simulate a market downturn as a negative shock on interest rate and credit market risk factors that reflect the b ...

We consider the numerical approximation of an optimal control problem for an elliptic Partial Differential Equation (PDE) with random coefficients. Specifically, the control function is a deterministic, distributed forcing term that minimizes the expected ...

Neighborhood-scale projects often commence with the conceptualization of several massing-schemes as potential design solutions. There is growing interest in using building performance simulation (BPS) to evaluate and rank such conceptual stage schemes in o ...

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

The aggregators are intermediary players at the distribution system level. They manage the financial transactions of resources such as micro-turbines (MTs), photo-voltaic (PV) production systems, flexible demands (FDs), and must-run demands (MDs) in the en ...

We investigate the willingness of individuals to persist at exploration in the face of failure. Prior research suggests that the organization's "tolerance for failure" may motivate greater exploration by the individual. Little is known, however, about how ...

Does the scaling relationship between population sizes of cities with urban metrics like economic output and infrastructure (transversal scaling) mirror the evolution of individual cities in time (longitudinal scaling)? The answer to this question has impo ...

We study stochastic programs where the decision-maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transfo ...

We investigate the problem of multi-agent coordination under rationality constraints. Specifically, role allocation, task assignment, resource allocation, etc. Inspired by human behavior, we propose a framework (CA^3NONY) that enables fast convergence to e ...

This thesis aims to further investigate rare natural disasters and studies adaptation decisions under uncertainty by solving several computational economic models. The modeling of rare natural disasters depends on the treatment of catastrophic outcomes wit ...

In the inter-war period, progressive architects confronted the building of mass housing with an analogy with rational and functional workplaces. At the 2nd CIAM (Congres Internationaux d'Architecture Moderne), held in Frankfurt in 1929, this was tested aga ...

In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an exogenous signal. Thus, the observer seeks the agent's objective function that best explains a historical ...

Landslides as secondary seismic effects are causing some patterns of soil failure that are often considered among the most destructive ones. In fact, the impact from triggered landslides has sometimes exceeded damage directly related to strong shaking and ...

We propose a method to design a decentralized energy market which guarantees individual rationality (IR) in expectation, in the presence of system-level grid constraints. We formulate the market as a welfare maximization problem subject to IR constraints, ...

Analyzing the Emergence of Semantic Agreement among Rational Agents

Chattez avec Graph Search

Stochastic adaptive resampling for the estimation of discrete choice models

Scalable Multi-agent Coordination and Resource Sharing

Improved Cooperation by Exploiting a Common Signal

Exploiting environmental signals to enable policy correlation in large-scale decentralized systems

Peer-Prediction in the Presence of Outcome Dependent Lying Incentives

Bridging the gap between model-driven and data-driven methods in the era of Big Data

Predicting the stressed expected loss of large US banks

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Impact of facade details on the reliability of performance-based decisions for early-stage neighborhood designs

Wasserstein Distributionally Robust Learning

Balancing management of strategic aggregators using non-cooperative game theory

Motivating Innovation: The Effect of Loss Aversion on the Willingness to Persist

On the relation between transversal and longitudinal scaling in cities

From Data to Decisions: Distributionally Robust Optimization is Optimal

Courtesy As a Means to Coordinate

Essays on adaptation to rare disasters

Moving on: Is Existenzminimum Still Relevant?

Data-Driven Inverse Optimization with Incomplete Information

Hazard and risk assessment of earthquake-induced landslides-case study

A rational decentralized generalized Nash equilibrium seeking for energy markets