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Subgame Optimal and Prior-Independent Online Algorithms arXiv.cs.GT Pub Date : 2024-03-15 Jason Hartline, Aleck Johnsen, Anant Shah
This paper takes a game theoretic approach to the design and analysis of online algorithms and illustrates the approach on the finite-horizon ski-rental problem. This approach allows beyond worst-case analysis of online algorithms. First, we define "subgame optimality" which is stronger than worst case optimality in that it requires the algorithm to take advantage of an adversary not playing a worst
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DDPS: Dynamic Differential Pricing-based Edge Offloading System with Energy Harvesting Devices arXiv.cs.GT Pub Date : 2024-03-15 Hai Xue, Yun Xia, Neal N. Xiong, Di Zhang, Songwen Pei
Mobile edge computing (MEC) paves the way to alleviate the burden of energy and computation of mobile users (MUs) by offloading tasks to the network edge. To enhance the MEC server utilization by optimizing its resource allocation, a well-designed pricing strategy is indispensable. In this paper, we consider the edge offloading scenario with energy harvesting devices, and propose a dynamic differential
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The Query Complexity of Contracts arXiv.cs.GT Pub Date : 2024-03-14 Paul Dütting, Michal Feldman, Yoav Gal-Tzur, Aviad Rubinstein
Algorithmic contract design is a new frontier in the intersection of economics and computation, with combinatorial contracts being a core problem in this domain. A central model within combinatorial contracts explores a setting where a principal delegates the execution of a task, which can either succeed or fail, to an agent. The agent can choose any subset among a given set of costly actions, where
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Sequential Contracts arXiv.cs.GT Pub Date : 2024-03-14 Tomer Ezra, Michal Feldman, Maya Schlesinger
We study the principal-agent setting, where a principal delegates the execution of a costly project to an agent. In the classical model, the agent chooses an action among a set of available actions. Every action is associated with some cost, and leads to a stochastic outcome for the project. The agent's action is hidden from the principal, who only observes the outcome. The principal incentivizes the
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All-pay Auction Based Profit Maximization in End-to-End Computation Offloading System arXiv.cs.GT Pub Date : 2024-03-14 Hai Xue, Yun Xia, Di Zhang, Honghua Wei, Xiaolong Xu
Pricing is an important issue in mobile edge computing. How to appropriately determine the bid of end user (EU) is an incentive factor for edge cloud (EC) to offer service. In this letter, we propose an equilibrium pricing scheme based on the all-pay auction model in end-to-end collaboration environment, wherein all EUs can acquire the service at a lower price than the own value of the required resource
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Data Monetization Pathways and Complex Dynamic Game Equilibrium Analysis in the Energy Industry arXiv.cs.GT Pub Date : 2024-03-12 Zongxian Wang, Jie Song
As the most critical production factor in the era of the digital economy, data will have a significant impact on social production and development. Energy enterprises possess data that is interconnected with multiple industries, characterized by diverse needs, sensitivity, and long-term nature. The path to monetizing energy enterprises' data is challenging yet crucial. This paper explores the game-theoretic
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Multi-Apartment Rent Division arXiv.cs.GT Pub Date : 2024-03-12 Ariel D. Procaccia, Benjamin Schiffer, Shirley Zhang
Rent division is the well-studied problem of fairly assigning rooms and dividing rent among a set of roommates within a single apartment. A shortcoming of existing solutions is that renters are assumed to be considering apartments in isolation, whereas in reality, renters can choose among multiple apartments. In this paper, we generalize the rent division problem to the multi-apartment setting, where
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The Flow Game: Leximin and Leximax Core Imputations arXiv.cs.GT Pub Date : 2024-03-09 Rohith R. Gangam, Naveen Garg, Parnian Shahkar, Vijay V. Vazirani
Recently [Vaz24] gave mechanisms for finding leximin and leximax core imputations for the assignment game and remarked, "Within the area of algorithm design, the "right" technique for solving several types of algorithmic questions was first discovered in the context of matching and later these insights were applied to other problems. We expect a similar phenomenon here." One of the games explicitly
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Synthesis of Robust Optimal Strategies in Weighted Timed Games arXiv.cs.GT Pub Date : 2024-03-11 Benjamin Monmege, Julie Parreaux, Pierre-Alain Reynier
Weighted Timed Games (WTG for short) are the most widely used model to describe controller synthesis problems involving real-time issues. The synthesized strategies rely on a perfect measure of time elapse, which is not realistic in practice. In order to produce strategies tolerant to timing imprecisions, we rely on a notion of robustness first introduced for timed automata. More precisely, WTGs are
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Pre- and Post-Auction Discounts in First-Price Auctions arXiv.cs.GT Pub Date : 2024-03-10 Miguel Alcobendas, Eric Bax
One method to offer some bidders a discount in a first-price auction is to augment their bids when selecting a winner but only charge them their original bids should they win. Another method is to use their original bids to select a winner, then charge them a discounted price that is lower than their bid should they win. We show that the two methods have equivalent auction outcomes, for equal additive
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Elections in the Post-Quantum Era: Is the Complexity Shield Strong Enough? arXiv.cs.GT Pub Date : 2024-03-08 Šimon Schierreich
The election, a cornerstone of democracy, is one of the best-recognizable symbols of democratic governance. Voters' confidence in elections is essential, and these days, we can watch practically in live broadcast what consequences distrust in the fairness of elections may have. From the times of the celebrated Gibbard-Satterthwaite theorem, it is well-known in the social-choice community that most
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A Task-Driven Multi-UAV Coalition Formation Mechanism arXiv.cs.GT Pub Date : 2024-03-08 Xinpeng Lu, Heng Song, Huailing Ma, Junwu Zhu
With the rapid advancement of UAV technology, the problem of UAV coalition formation has become a hotspot. Therefore, designing task-driven multi-UAV coalition formation mechanism has become a challenging problem. However, existing coalition formation mechanisms suffer from low relevance between UAVs and task requirements, resulting in overall low coalition utility and unstable coalition structures
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Safe Pareto Improvements for Expected Utility Maximizers in Program Games arXiv.cs.GT Pub Date : 2024-03-08 Anthony DiGiovanni, Jesse Clifton
Agents in mixed-motive coordination problems such as Chicken may fail to coordinate on a Pareto-efficient outcome. Safe Pareto improvements (SPIs) were originally proposed to mitigate miscoordination in cases where players lack probabilistic beliefs as to how their delegates will play a game; delegates are instructed to behave so as to guarantee a Pareto improvement on how they would play by default
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Winner-Pays-Bid Auctions Minimize Variance arXiv.cs.GT Pub Date : 2024-03-07 Preston McAfee, Renato Paes Leme, Balasubramanian Sivan, Sergei Vassilvitskii
Any social choice function (e.g the efficient allocation) can be implemented using different payment rules: first price, second price, all-pay, etc. All of these payment rules are guaranteed to have the same expected revenue by the revenue equivalence theorem, but have different distributions of revenue, leading to a question of which one is best. We prove that among all possible payment rules, winner-pays-bid
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Mechanism for Decision-aware Collaborative Federated Learning: A Pitfall of Shapley Values arXiv.cs.GT Pub Date : 2024-03-07 Meng Qi, Mingxi Zhu
This paper investigates mechanism design for decision-aware collaboration via federated learning (FL) platforms. Our framework consists of a digital platform and multiple decision-aware agents, each endowed with proprietary data sets. The platform offers an infrastructure that enables access to the data, creates incentives for collaborative learning aimed at operational decision-making, and conducts
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Extensive-Form Game Solving via Blackwell Approachability on Treeplexes arXiv.cs.GT Pub Date : 2024-03-07 Darshan Chakrabarti, Julien Grand-Clément, Christian Kroer
In this paper, we introduce the first algorithmic framework for Blackwell approachability on the sequence-form polytope, the class of convex polytopes capturing the strategies of players in extensive-form games (EFGs). This leads to a new class of regret-minimization algorithms that are stepsize-invariant, in the same sense as the Regret Matching and Regret Matching$^+$ algorithms for the simplex.
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Modeling reputation-based behavioral biases in school choice arXiv.cs.GT Pub Date : 2024-03-07 Jon Kleinberg, Sigal Oren, Emily Ryu, Éva Tardos
A fundamental component in the theoretical school choice literature is the problem a student faces in deciding which schools to apply to. Recent models have considered a set of schools of different selectiveness and a student who is unsure of their strength and can apply to at most $k$ schools. Such models assume that the student cares solely about maximizing the quality of the school that they attend
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Empirical Game-Theoretic Analysis: A Survey arXiv.cs.GT Pub Date : 2024-03-06 Michael P. Wellman, Karl Tuyls, Amy Greenwald
In the empirical approach to game-theoretic analysis (EGTA), the model of the game comes not from declarative representation, but is derived by interrogation of a procedural description of the game environment. The motivation for developing this approach was to enable game-theoretic reasoning about strategic situations too complex for analytic specification and solution. Since its introduction over
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Settling the Competition Complexity of Additive Buyers over Independent Items arXiv.cs.GT Pub Date : 2024-03-06 Mahsa Derakhshan, Emily Ryu, S. Matthew Weinberg, Eric Xue
The competition complexity of an auction setting is the number of additional bidders needed such that the simple mechanism of selling items separately (with additional bidders) achieves greater revenue than the optimal but complex (randomized, prior-dependent, Bayesian-truthful) optimal mechanism without the additional bidders. Our main result settles the competition complexity of $n$ bidders with
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To Trust or Not to Trust: Assignment Mechanisms with Predictions in the Private Graph Model arXiv.cs.GT Pub Date : 2024-03-06 Riccardo Colini-Baldeschi, Sophie Klumper, Guido Schäfer, Artem Tsikiridis
The realm of algorithms with predictions has led to the development of several new algorithms that leverage (potentially erroneous) predictions to enhance their performance guarantees. The challenge is to devise algorithms that achieve optimal approximation guarantees as the prediction quality varies from perfect (consistency) to imperfect (robustness). This framework is particularly appealing in mechanism
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Application of Nash equilibrium for developing an optimal forest harvesting strategy in Toruń Forest District arXiv.cs.GT Pub Date : 2024-03-06 Jan Kotlarz
This study investigates the application of Nash equilibrium strategies in optimizing forest harvesting decisions, focusing on multiple management objectives in forestry. Through simulation-based analysis, the research explores the evolution of various indicators during the game: 1) the mass of CO2 sequestration, 2) forest stands biodiversity, 3) the harvested wood volume, 4) native species fraction
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Adaptive coordination promotes collective cooperation in repeated social dilemmas arXiv.cs.GT Pub Date : 2024-03-06 Feipeng Zhang, Te Wu, Long Wang
Direct reciprocity based on the repeated prisoner's dilemma has been intensively studied. Most theoretical investigations have concentrated on memory-$1$ strategies, a class of elementary strategies just reacting to the previous-round outcomes. Though the properties of "All-or-None" strategies ($AoN_K$) have been discovered, simulations just confirmed the good performance of $AoN_K$ of very short memory
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Equilibria in Two-Stage Facility Location with Atomic Clients arXiv.cs.GT Pub Date : 2024-03-05 Simon Krogmann, Pascal Lenzner, Alexander Skopalik, Marc Uetz, Marnix C. Vos
We consider competitive facility location as a two-stage multi-agent system with two types of clients. For a given host graph with weighted clients on the vertices, first facility agents strategically select vertices for opening their facilities. Then, the clients strategically select which of the opened facilities in their neighborhood to patronize. Facilities want to attract as much client weight
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MEBS: Multi-task End-to-end Bid Shading for Multi-slot Display Advertising arXiv.cs.GT Pub Date : 2024-03-05 Zhen Gong, Lvyin Niu, Yang Zhao, Miao Xu, Zhenzhe Zheng, Haoqi Zhang, Zhilin Zhang, Fan Wu, Rongquan Bai, Chuan Yu, Jian Xu, Bo Zheng
Online bidding and auction are crucial aspects of the online advertising industry. Conventionally, there is only one slot for ad display and most current studies focus on it. Nowadays, multi-slot display advertising is gradually becoming popular where many ads could be displayed in a list and shown as a whole to users. However, multi-slot display advertising leads to different cost-effectiveness. Advertisers
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An Analysis of Intent-Based Markets arXiv.cs.GT Pub Date : 2024-03-04 Tarun Chitra, Kshitij Kulkarni, Mallesh Pai, Theo Diamandis
Mechanisms for decentralized finance on blockchains suffer from various problems, including suboptimal price execution for users, latency, and a worse user experience compared to their centralized counterparts. Recently, off-chain marketplaces, colloquially called `intent markets,' have been proposed as a solution to these problems. In these markets, agents called \emph{solvers} compete to satisfy
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Envy-Free House Allocation with Minimum Subsidy arXiv.cs.GT Pub Date : 2024-03-02 Davin Choo, Yan Hao Ling, Warut Suksompong, Nicholas Teh, Jian Zhang
House allocation refers to the problem where $m$ houses are to be allocated to $n$ agents so that each agent receives one house. Since an envy-free house allocation does not always exist, we consider finding such an allocation in the presence of subsidy. We show that computing an envy-free allocation with minimum subsidy is NP-hard in general, but can be done efficiently if $m$ differs from $n$ by
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Public Projects with Preferences and Predictions arXiv.cs.GT Pub Date : 2024-03-02 Mary Monroe, Bo Waggoner
In the public projects problem, a group of decisionmakers aggregate their preferences to choose one alternative. Recent work on public projects has proposed the Quadratic Transfers Mechanism (QTM) and shown asymptotic welfare guarantees in some cases. We begin by giving new non-asymptotic Price of Anarchy guarantees for the QTM. We then incorporate an alternative philosophy toward group decisionmaking
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On the Hardness of Fair Allocation under Ternary Valuations arXiv.cs.GT Pub Date : 2024-03-01 Zack Fitzsimmons, Vignesh Viswanathan, Yair Zick
We study the problem of fair allocation of indivisible items when agents have ternary additive valuations -- each agent values each item at some fixed integer values $a$, $b$, or $c$ that are common to all agents. The notions of fairness we consider are max Nash welfare (MNW), when $a$, $b$, and $c$ are non-negative, and max egalitarian welfare (MEW). We show that for any distinct non-negative $a$
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Dynamic Operational Planning in Warfare: A Stochastic Game Approach to Military Campaigns arXiv.cs.GT Pub Date : 2024-03-01 Joseph E. McCarthy, Mathieu Dahan, Chelsea C. White III
We study a two-player discounted zero-sum stochastic game model for dynamic operational planning in military campaigns. At each stage, the players manage multiple commanders who order military actions on objectives that have an open line of control. When a battle over the control of an objective occurs, its stochastic outcome depends on the actions and the enabling support provided by the control of
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As Soon as Possible but Rationally arXiv.cs.GT Pub Date : 2024-03-01 Véronique Bruyère, Christophe Grandmont, Jean-François Raskin
This paper addresses complexity problems in rational verification and synthesis for multi-player games played on weighted graphs, where the objective of each player is to minimize the cost of reaching a specific set of target vertices. In these games, one player, referred to as the system, declares his strategy upfront. The other players, composing the environment, then rationally make their moves
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The Price of Fairness in Bipartite Matching arXiv.cs.GT Pub Date : 2024-03-01 Rémi Castera, Felipe Garrido-Lucero, Mathieu Molina, Simon Mauras, Patrick Loiseau, Vianney Perchet
We investigate notions of group fairness in bipartite matching markets involving agents and jobs, where agents are grouped based on sensitive attributes. Employing a geometric approach, we characterize how many agents can be matched in each group, showing that the set of feasible matchings forms a (discrete) polymatroid. We show how we can define weakly-fair matchings geometrically, for which poly-matroid
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Fundamental Limits of Throughput and Availability: Applications to prophet inequalities & transaction fee mechanism design arXiv.cs.GT Pub Date : 2024-02-29 Aadityan Ganesh, Jason Hartline, Atanu R Sinha, Matthew vonAllmen
This paper studies the fundamental limits of availability and throughput for independent and heterogeneous demands of a limited resource. Availability is the probability that the demands are below the capacity of the resource. Throughput is the expected fraction of the resource that is utilized by the demands. We offer a concentration inequality generator that gives lower bounds on feasible availability
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The Cost of Permissionless Liquidity Provision in Automated Market Makers arXiv.cs.GT Pub Date : 2024-02-28 Julian Ma, Davide Crapis
Automated market makers (AMMs) allocate fee revenue proportional to the amount of liquidity investors deposit. In this paper, we study the economic consequences of the competition between passive liquidity providers (LPs) caused by this allocation rule. We employ a game-theoretic model in which $N$ strategic agents optimally provide liquidity. In this setting, we find that competition drives LPs to
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Mixed Strategy Constraints in Continuous Games arXiv.cs.GT Pub Date : 2024-02-27 Mel Krusniak, Forrest Laine
Equilibrium problems representing interaction in physical environments typically require continuous strategies which satisfy opponent-dependent constraints, such as those modeling collision avoidance. However, as with finite games, mixed strategies are often desired, both from an equilibrium existence perspective as well as a competitive perspective. To that end, this work investigates a chance-constraint-based
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Increasing the Diversity of Investment Portfolio with Integration of Gamified Components in the FinTech Applications Lifecycle arXiv.cs.GT Pub Date : 2024-02-27 Latifeh PourMohammadBagher, Najmieh Sadat Safarabadi
Gamification has the potential to make significant contributions to financial product delivery, Fintech services, and inclusive growth. The integration of gamification into FinTech applications has shown a positive correlation with the social impact theory. Utilizing gamification in a sustainable and effective manner can be crucial for long-term prospects in the FinTech industry. Therefore, it is essential
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Weighted EF1 and PO Allocations with Few Types of Agents or Chores arXiv.cs.GT Pub Date : 2024-02-27 Jugal Garg, Aniket Murhekar, John Qin
We investigate the existence of fair and efficient allocations of indivisible chores to asymmetric agents who have unequal entitlements or weights. We consider the fairness notion of weighted envy-freeness up to one chore (wEF1) and the efficiency notion of Pareto-optimality (PO). The existence of EF1 and PO allocations of chores to symmetric agents is a major open problem in discrete fair division
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Optimal Mechanisms for Consumer Surplus Maximization arXiv.cs.GT Pub Date : 2024-02-26 Tomer Ezra, Daniel Schoepflin, Ariel Shaulker
We consider the problem of designing auctions which maximize consumer surplus (i.e., the social welfare minus the payments charged to the buyers). In the consumer surplus maximization problem, a seller with a set of goods faces a set of strategic buyers with private values, each of whom aims to maximize their own individual utility. The seller, in contrast, aims to allocate the goods in a way which
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Contracts with Inspections arXiv.cs.GT Pub Date : 2024-02-26 Tomer Ezra, Stefano Leonardi, Matteo Russo
In the classical principal-agent hidden-action model, a principal delegates the execution of a costly task to an agent for which he can choose among actions with different costs and different success probabilities to accomplish the task. To incentivize the agent to exert effort, the principal can commit to a contract, which is the amount of payment based on the task's success. A crucial assumption
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Agent-Designed Contracts: How to Sell Hidden Actions arXiv.cs.GT Pub Date : 2024-02-26 Martino Bernasconi, Matteo Castiglioni, Andrea Celli
We study the problem faced by a service provider that has to sell services to a user. In our model the service provider proposes various payment options (a menu) to the user which may be based, for example, on the quality of the service. Then, the user chooses one of these options and pays an amount to the service provider, contingent on the observed final outcome. Users are not able to observe directly
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Fast, Fair and Truthful Distributed Stable Matching for Common Preferences arXiv.cs.GT Pub Date : 2024-02-26 Juho Hirvonen, Sara Ranjbaran
Stable matching is a fundamental problem studied both in economics and computer science. The task is to find a matching between two sides of agents that have preferences over who they want to be matched with. A matching is stable if no pair of agents prefer each other over their current matches. The deferred acceptance algorithm of Gale and Shapley solves this problem in polynomial time. Further, it
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Polynomial-Time Computation of Exact $Φ$-Equilibria in Polyhedral Games arXiv.cs.GT Pub Date : 2024-02-26 Gabriele Farina, Charilaos Pipis
It is a well-known fact that correlated equilibria can be computed in polynomial time in a large class of concisely represented games using the celebrated Ellipsoid Against Hope algorithm (Papadimitriou and Roughgarden, 2008; Jiang and Leyton-Brown, 2015). However, the landscape of efficiently computable equilibria in sequential (extensive-form) games remains unknown. The Ellipsoid Against Hope does
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Complexity of Manipulation and Bribery in Premise-Based Judgment Aggregation with Simple Formulas arXiv.cs.GT Pub Date : 2024-02-25 Robert Bredereck, Junjie Luo
Judgment aggregation is a framework to aggregate individual opinions on multiple, logically connected issues into a collective outcome. It is open to manipulative attacks such as \textsc{Manipulation} where judges cast their judgments strategically. Previous works have shown that most computational problems corresponding to these manipulative attacks are \NP-hard. This desired computational barrier
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Differentially Private Bayesian Persuasion arXiv.cs.GT Pub Date : 2024-02-24 Yuqi Pan, Zhiwei Steven Wu, Haifeng Xu, Shuran Zheng
The tension between persuasion and privacy preservation is common in real-world settings. Online platforms should protect the privacy of web users whose data they collect, even as they seek to disclose information about these data to selling advertising spaces. Similarly, hospitals may share patient data to attract research investments with the obligation to preserve patients' privacy. To deal with
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Measuring Bargaining Abilities of LLMs: A Benchmark and A Buyer-Enhancement Method arXiv.cs.GT Pub Date : 2024-02-24 Tian Xia, Zhiwei He, Tong Ren, Yibo Miao, Zhuosheng Zhang, Yang Yang, Rui Wang
Bargaining is an important and unique part of negotiation between humans. As LLM-driven agents learn to negotiate and act like real humans, how to evaluate agents' bargaining abilities remains an open problem. For the first time, we formally described the Bargaining task as an asymmetric incomplete information game, defining the gains of the Buyer and Seller in multiple bargaining processes. It allows
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On the Fairness of Normalized p-Means for Allocating Goods and Chores arXiv.cs.GT Pub Date : 2024-02-22 Owen Eckart, Alexandros Psomas, Paritosh Verma
Allocating items in a fair and economically efficient manner is a central problem in fair division. We study this problem for agents with additive preferences, when items are all goods or all chores, divisible or indivisible. The celebrated notion of Nash welfare is known to produce fair and efficient allocations for both divisible and indivisible goods; there is no known analogue for dividing chores
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On Truthful Item-Acquiring Mechanisms for Reward Maximization arXiv.cs.GT Pub Date : 2024-02-22 Liang Shan, Shuo Zhang, Jie Zhang, Zihe Wang
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 collector acquires the items and is the only one who knows the items' factual quality. The appraiser performs her duties with impartiality, but her assessment may
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Tight Inapproximability of Nash Equilibria in Public Goods Games arXiv.cs.GT Pub Date : 2024-02-22 Jérémi Do Dinh, Alexandros Hollender
We study public goods games, a type of game where every player has to decide whether or not to produce a good which is public, i.e., neighboring players can also benefit from it. Specifically, we consider a setting where the good is indivisible and where the neighborhood structure is represented by a directed graph, with the players being the nodes. Papadimitriou and Peng (2023) recently showed that
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Fairness and Incentive Compatibility via Percentage Fees arXiv.cs.GT Pub Date : 2024-02-21 Shahar Dobzinski, Sigal Oren, Jan Vondrak
We study incentive-compatible mechanisms that maximize the Nash Social Welfare. Since traditional incentive-compatible mechanisms cannot maximize the Nash Social Welfare even approximately, we propose changing the traditional model. Inspired by a widely used charging method (e.g., royalties, a lawyer that charges some percentage of possible future compensation), we suggest charging the players some
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Information Elicitation in Agency Games arXiv.cs.GT Pub Date : 2024-02-21 Serena Wang, Michael I. Jordan, Katrina Ligett, R. Preston McAfee
Rapid progress in scalable, commoditized tools for data collection and data processing has made it possible for firms and policymakers to employ ever more complex metrics as guides for decision-making. These developments have highlighted a prevailing challenge -- deciding *which* metrics to compute. In particular, a firm's ability to compute a wider range of existing metrics does not address the problem
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Equilibria, Efficiency, and Inequality in Network Formation for Hiring and Opportunity arXiv.cs.GT Pub Date : 2024-02-21 Cynthia Dwork, Chris Hays, Jon Kleinberg, Manish Raghavan
Professional networks -- the social networks among people in a given line of work -- can serve as a conduit for job prospects and other opportunities. Here we propose a model for the formation of such networks and the transfer of opportunities within them. In our theoretical model, individuals strategically connect with others to maximize the probability that they receive opportunities from them. We
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Multi-Agent Contract Design beyond Binary Actions arXiv.cs.GT Pub Date : 2024-02-21 Federico Cacciamani, Martino Bernasconi, Matteo Castiglioni, Nicola Gatti
We study hidden-action principal-agent problems with multiple agents. Unlike previous work, we consider a general setting in which each agent has an arbitrary number of actions, and the joint action induces outcomes according to an arbitrary distribution. We study two classes of mechanisms: a class of deterministic mechanisms that is the natural extension of single-agent contracts, in which the agents
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Algorithms for Claims Trading arXiv.cs.GT Pub Date : 2024-02-21 Martin Hoefer, Carmine Ventre, Lisa Wilhelmi
The recent banking crisis has again emphasized the importance of understanding and mitigating systemic risk in financial networks. In this paper, we study a market-driven approach to rescue a bank in distress based on the idea of claims trading, a notion defined in Chapter 11 of the U.S. Bankruptcy Code. We formalize the idea in the context of financial networks by Eisenberg and Noe. For two given
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Spot Check Equivalence: an Interpretable Metric for Information Elicitation Mechanisms arXiv.cs.GT Pub Date : 2024-02-21 Shengwei Xu, Yichi Zhang, Paul Resnick, Grant Schoenebeck
Because high-quality data is like oxygen for AI systems, effectively eliciting information from crowdsourcing workers has become a first-order problem for developing high-performance machine learning algorithms. Two prevalent paradigms, spot-checking and peer prediction, enable the design of mechanisms to evaluate and incentivize high-quality data from human labelers. So far, at least three metrics
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Stable matching as transportation arXiv.cs.GT Pub Date : 2024-02-20 Federico Echenique, Joseph Root, Fedor Sandomirskiy
We study matching markets with aligned preferences and establish a connection between common design objectives -- stability, efficiency, and fairness -- and the theory of optimal transport. Optimal transport gives new insights into the structural properties of matchings obtained from pursuing these objectives, and into the trade-offs between different objectives. Matching markets with aligned preferences
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Regret-Minimizing Contracts: Agency Under Uncertainty arXiv.cs.GT Pub Date : 2024-02-20 Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi
We study the fundamental problem of designing contracts in principal-agent problems under uncertainty. Previous works mostly addressed Bayesian settings in which principal's uncertainty is modeled as a probability distribution over agent's types. In this paper, we study a setting in which the principal has no distributional information about agent's type. In particular, in our setting, the principal
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MORE-3S:Multimodal-based Offline Reinforcement Learning with Shared Semantic Spaces arXiv.cs.GT Pub Date : 2024-02-20 Tianyu Zheng, Ge Zhang, Xingwei Qu, Ming Kuang, Stephen W. Huang, Zhaofeng He
Drawing upon the intuition that aligning different modalities to the same semantic embedding space would allow models to understand states and actions more easily, we propose a new perspective to the offline reinforcement learning (RL) challenge. More concretely, we transform it into a supervised learning task by integrating multimodal and pre-trained language models. Our approach incorporates state
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Simple Mechanisms for Utility Maximization: Approximating Welfare in the I.I.D. Unit-Demand Setting arXiv.cs.GT Pub Date : 2024-02-19 Kira Goldner, Taylor Lundy
We investigate the objective of utility maximization from the perspective of Bayesian mechanism design, initiating this direction, and focus on the unit-demand setting where values are i.i.d. across both items and buyers. We take the approach of developing simple, approximately optimal mechanisms, targeting the simplest benchmark of optimal welfare. We give a $(1-1/e)$-approximation when there are
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Integrating Dynamic Weighted Approach with Fictitious Play and Pure Counterfactual Regret Minimization for Equilibrium Finding arXiv.cs.GT Pub Date : 2024-02-19 Qi Ju, Falin Hei, Zhemei Fang, Yunfeng Luo
Developing efficient algorithms to converge to Nash Equilibrium is a key focus in game theory. The use of dynamic weighting has been especially advantageous in normal-form games, enhancing the rate of convergence. For instance, the Greedy Regret Minimization (RM) algorithm has markedly outperformed earlier techniques. Nonetheless, its dependency on mixed strategies throughout the iterative process
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On the Computation of Equilibria in Discrete First-Price Auctions arXiv.cs.GT Pub Date : 2024-02-19 Aris Filos-Ratsikas, Yiannis Giannakopoulos, Alexandros Hollender, Charalampos Kokkalis
We study the computational complexity of computing Bayes-Nash equilibria in first-price auctions with discrete value distributions and discrete bidding space, under general subjective beliefs. It is known that such auctions do not always have pure equilibria. In this paper we prove that the problem of deciding their existence is NP-complete, even for approximate equilibria. On the other hand, it can
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Modifying an Instance of the Super-Stable Matching Problem arXiv.cs.GT Pub Date : 2024-02-19 Naoyuki Kamiyama
Super-stability is one of the stability concepts in the stable matching problem with ties. It is known that there may not exist a super-stable matching, and the existence of a super-stable matching can be checked in polynomial time. In this paper, we consider the problem of modifying an instance of the super-stable matching problem by deleting some bounded number of agents in such a way that there