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We study principal-agent problems in which a principal commits to an outcome-dependent payment scheme (a.k.a. contract) so as to induce an agent to take a costly, unobservable action. We relax the assumption that the principal perfectly…

Computer Science and Game Theory · Computer Science 2021-06-02 Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

We study principal-agent problems in which a principal commits to an outcome-dependent payment scheme -- called contract -- in order to induce an agent to take a costly, unobservable action leading to favorable outcomes. We consider a…

Computer Science and Game Theory · Computer Science 2024-06-10 Francesco Bacchiocchi , Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

Multi-agent distributed consensus optimization problems arise in many signal processing applications. Recently, the alternating direction method of multipliers (ADMM) has been used for solving this family of problems. ADMM based distributed…

Systems and Control · Computer Science 2015-06-18 Tsung-Hui Chang , Mingyi Hong , Xiangfeng Wang

We consider an agent community wishing to decide on several binary issues by means of issue-by-issue majority voting. For each issue and each agent, one of the two options is better than the other. However, some of the agents may be…

Computer Science and Game Theory · Computer Science 2022-07-12 Shiri Alouf-Heffetz , Laurent Bulteau , Edith Elkind , Nimrod Talmon , Nicholas Teh

In online combinatorial allocation, agents arrive sequentially and items are allocated in an online manner. The algorithm designer only knows the distribution of each agent's valuation, while the actual realization of the valuation is…

Data Structures and Algorithms · Computer Science 2025-10-14 Enze Sun , Zhihao Gavin Tang , Yifan Wang

The problem of computing near-optimal contracts in combinatorial settings has recently attracted significant interest in the computer science community. Previous work has provided a rich body of structural and algorithmic insights into this…

Computer Science and Game Theory · Computer Science 2025-06-26 Michal Feldman , Yoav Gal-Tzur , Tomasz Ponitka , Maya Schlesinger

We propose a fully differentiable architecture for simultaneous semantic and instance segmentation (a.k.a. panoptic segmentation) consisting of a convolutional neural network and an asymmetric multiway cut problem solver. The latter solves…

Computer Vision and Pattern Recognition · Computer Science 2021-10-26 Ahmed Abbas , Paul Swoboda

The purpose of this note is to survey a methodology to solve systems of polynomial equations and inequalities. The techniques we discuss use the algebra of multivariate polynomials with coefficients over a field to create large-scale linear…

Optimization and Control · Mathematics 2011-12-08 Jesus A. De Loera , Peter N. Malkin , Pablo A. Parrilo

This paper fully studies distributed optimal consensus problem in non-directed dynamical networks. We consider a group of networked agents that are supposed to rendezvous at the optimal point of a collective convex objective function. Each…

Optimization and Control · Mathematics 2017-12-22 Amir Adibzadeh , Amir A. Suratgar , Mohammad B. Menhaja , Mohsen Zamani

A general nonlinear $1$st-order consensus-based solution for distributed constrained convex optimization is proposed with network resource allocation applications. The solution is used to optimize continuously-differentiable strictly convex…

Systems and Control · Electrical Eng. & Systems 2021-11-22 Mohammadreza Doostmohammadian , Alireza Aghasi , Maria Vrakopoulou , Themistoklis Charalambous

Consider a principal who wants to search through a space of stochastic solutions for one maximizing their utility. If the principal cannot conduct this search on their own, they may instead delegate this problem to an agent with distinct…

Computer Science and Game Theory · Computer Science 2024-11-04 Curtis Bechtel , Shaddin Dughmi

We analyze conditional optimization problems arising in discrete time Principal-Agent problems of delegated portfolio optimization with linear contracts. Applying tools from Conditional Analysis we show that some results known in the…

Mathematical Finance · Quantitative Finance 2016-06-15 Julio Backhoff , Ulrich Horst

The challenge of finding compromises between agent proposals is fundamental to AI subfields such as argumentation, mediation, and negotiation. Building on this tradition, Elkind et al. (2021) introduced a process for coalition formation…

Multiagent Systems · Computer Science 2026-04-01 Eyal Briman , Ehud Shapiro , Nimrod Talmon

In the combinatorial action model of contract design, a principal delegates a complex project to an agent, incentivizing a subset of actions from a ground set of $n$ actions, via a linear contract. Computing the optimal contract is a…

Computer Science and Game Theory · Computer Science 2026-04-17 Elizabeth Baldwin , Paul Duetting , Michal Feldman , Maya Schlesinger

This paper introduces a new negotiating agent model for automated negotiation. We focus on applications without time pressure with multidi-mensional negotiation on both continuous and discrete domains. The agent bidding strategy relies on…

Multiagent Systems · Computer Science 2019-09-23 Cédric Buron , Zahia Guessoum , Sylvain Ductor

We introduce a dynamic mechanism design problem in which the designer wants to offer for sale an item to an agent, and another item to the same agent at some point in the future. The agent's joint distribution of valuations for the two…

Computer Science and Game Theory · Computer Science 2023-05-22 Christos Papadimitriou , George Pierrakos , Christos-Alexandros Psomas , Aviad Rubinstein

The search for information on the web is faced with several problems, which arise on the one hand from the vast number of available sources, and on the other hand from their heterogeneity. A promising approach is the use of multi-agent…

Multiagent Systems · Computer Science 2007-05-23 T. Eiter , M. Fink , G. Sabbatini , H. Tompits

This paper proposes a new combinatorial auction framework for local energy flexibility markets, which addresses the issue of prosumers' inability to bundle multiple flexibility time intervals. To solve the underlying NP-complete winner…

Machine Learning · Computer Science 2023-07-27 Awadelrahman M. A. Ahmed , Frank Eliassen , Yan Zhang

Resource balancing within complex transportation networks is one of the most important problems in real logistics domain. Traditional solutions on these problems leverage combinatorial optimization with demand and supply forecasting.…

Multiagent Systems · Computer Science 2019-03-05 Xihan Li , Jia Zhang , Jiang Bian , Yunhai Tong , Tie-Yan Liu

Given a network of agents, we study the problem of designing a distributed algorithm that computes k independent weighted means of the network's initial conditions (namely, the agents agree on a k-dimensional space). Akin to average…

Optimization and Control · Mathematics 2024-10-23 Gianluca Bianchin , Miguel Vaquero , Jorge Cortes , Emiliano Dall'Anese
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