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In adversarial settings, a mobile agent may strategically plan its motion to influence an opponent's inference about its intended goal. We study deceptive path planning in a scenario where a mobile agent aims to reach a privately selected…

Systems and Control · Electrical Eng. & Systems 2026-05-19 Violetta Rostobaya , Yue Guan , James Berneburg , Daigo Shishika

Randomized experiments can be susceptible to selection bias due to potential non-compliance by the participants. While much of the existing work has studied compliance as a static behavior, we propose a game-theoretic model to study…

Machine Learning · Computer Science 2021-07-29 Daniel Ngo , Logan Stapleton , Vasilis Syrgkanis , Zhiwei Steven Wu

In this work, we study spectrum auction problem where each request from secondary users has spatial, temporal, and spectral features. With the requests of secondary users and the reserve price of the primary user, our goal is to design…

Networking and Internet Architecture · Computer Science 2013-05-29 Yu-e Sun , He Huang , Xiang-Yang Li , Zhili Chen , Wei Yang , Hongli Xu , Liusheng Huang

We study the problem of fairly allocating indivisible goods to groups of agents. Agents in the same group share the same set of goods even though they may have different preferences. Previous work has focused on unanimous fairness, in which…

Computer Science and Game Theory · Computer Science 2020-01-01 Erel Segal-Halevi , Warut Suksompong

Behavioral skills or policies for autonomous agents are conventionally learned from reward functions, via reinforcement learning, or from demonstrations, via imitation learning. However, both modes of task specification have their…

Matching users based on mutual preferences is a fundamental aspect of services driven by reciprocal recommendations, such as job search and dating applications. Although A/B tests remain the gold standard for evaluating new policies in…

Machine Learning · Computer Science 2025-07-21 Yudai Hayashi , Shuhei Goda , Yuta Saito

We consider the fundamental scenario where a single item is to be sold to one of two agents. Both agents draw their valuation for the item from the same probability distribution. However, only one of them submits a bid to the mechanism. The…

Computer Science and Game Theory · Computer Science 2025-08-26 Ioannis Caragiannis , Georgios Kalantzis

Consider the object allocation (one-sided matching) model of Shapley and Scarf (1974). When final allocations are observed but agents' preferences are unknown, when might the allocation be in the core? This is a one-sided analogue of the…

Theoretical Economics · Economics 2023-08-08 Andrew Tai

In this research, we study the problem that a collector acquires items from the owner based on the item qualities the owner declares and an independent appraiser's assessments. The owner is interested in maximizing the probability that the…

Computer Science and Game Theory · Computer Science 2024-02-23 Liang Shan , Shuo Zhang , Jie Zhang , Zihe Wang

A principal who values an object allocates it to one or more agents. Agents learn private information (signals) from an information designer about the allocation payoff to the principal. Monetary transfer is not available but the principal…

Theoretical Economics · Economics 2022-10-31 Yi-Chun Chen , Gaoji Hu , Xiangqian Yang

We consider a new setting of facility location games with ordinal preferences. In such a setting, we have a set of agents and a set of facilities. Each agent is located on a line and has an ordinal preference over the facilities. Our goal…

Computer Science and Game Theory · Computer Science 2021-07-06 Hau Chan , Minming Li , Chenhao Wang

Bayesian optimization (BO) is a powerful black-box optimization framework that looks to efficiently learn the global optimum of an unknown system by systematically trading-off between exploration and exploitation. However, the use of BO as…

Optimization and Control · Mathematics 2023-03-28 Dinesh Krishnamoorthy , Joel A. Paulson

In recommendation settings, there is an apparent trade-off between the goals of accuracy (to recommend items a user is most likely to want) and diversity (to recommend items representing a range of categories). As such, real-world…

Information Retrieval · Computer Science 2023-07-31 Kenny Peng , Manish Raghavan , Emma Pierson , Jon Kleinberg , Nikhil Garg

We study the fair division problem on divisible heterogeneous resources (the cake cutting problem) with strategic agents, where each agent can manipulate his/her private valuation in order to receive a better allocation. A…

Computer Science and Game Theory · Computer Science 2023-03-31 Xiaolin Bu , Jiaxin Song , Biaoshuai Tao

Organizations often rely on statistical algorithms to make socially and economically impactful decisions. We must address the fairness issues in these important automated decisions. On the other hand, economic efficiency remains…

Methodology · Statistics 2025-04-15 Jianqing Fan , Xin Tong , Yanhui Wu , Lucy Xia , Shunan Yao

An agent-based model for financial markets has to incorporate two aspects: decision making and price formation. We introduce a simple decision model and consider its implications in two different pricing schemes. First, we study its…

Trading and Market Microstructure · Quantitative Finance 2015-06-19 Daniel C. Wagner , Thilo A. Schmitt , Rudi Schäfer , Thomas Guhr , Dietrich E. Wolf

Direct alignment algorithms have proven an effective step for aligning language models to human-desired behaviors. Current variants of the Direct Preference Optimization objective have focused on a strict setting where all tokens are…

Computation and Language · Computer Science 2025-11-03 Fenia Christopoulou , Ronald Cardenas , Gerasimos Lampouras , Haitham Bou-Ammar , Jun Wang

We study the Price of Anarchy of mechanisms for the well-known problem of one-sided matching, or house allocation, with respect to the social welfare objective. We consider both ordinal mechanisms, where agents submit preference lists over…

Computer Science and Game Theory · Computer Science 2016-03-01 George Christodoulou , Aris Filos-Ratsikas , Soren Kristoffer Stiil Frederiksen , Paul W. Goldberg , Jie Zhang , Jinshan Zhang

We study the design of information acquisition games-environments where a designer contracts their action on Sender's choice of experiment and the realized signals about some state-and identify which predictions can be made absent knowledge…

Theoretical Economics · Economics 2026-01-22 Eric Gao , Daniel Luo

We study the problem of how to coordinate the actions of independent agents in a distributed system where message arrival times are unbounded, but are determined by an exponential probability distribution. Asynchronous protocols executed in…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-10 Ariel Livshits , Yoram Moses