arXiv - CS - Computer Science and Game Theory最新文献_第7页

On Rider Strategic Behavior in Ride-Sharing Platforms 论共享乘车平台上的乘客策略行为

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-08 DOI: arxiv-2408.04272

Jay Mulay, Diptangshu Sen, Juba Ziani

{"title":"On Rider Strategic Behavior in Ride-Sharing Platforms","authors":"Jay Mulay, Diptangshu Sen, Juba Ziani","doi":"arxiv-2408.04272","DOIUrl":"https://doi.org/arxiv-2408.04272","url":null,"abstract":"Over the past decade, ride-sharing services have become increasingly\u0000important, with U.S. market leaders such as Uber and Lyft expanding to over 900\u0000cities worldwide and facilitating billions of rides annually. This rise\u0000reflects their ability to meet users' convenience, efficiency, and\u0000affordability needs. However, in busy areas and surge zones, the benefits of\u0000these platforms can diminish, prompting riders to relocate to cheaper, more\u0000convenient locations or seek alternative transportation. While much research has focused on the strategic behavior of drivers, the\u0000strategic actions of riders, especially when it comes to riders walking outside\u0000of surge zones, remain under-explored. This paper examines the impact of\u0000rider-side strategic behavior on surge dynamics. We investigate how riders'\u0000actions influence market dynamics, including supply, demand, and pricing. We\u0000show significant impacts, such as spillover effects where demand increases in\u0000areas adjacent to surge zones and prices surge in nearby areas. Our theoretical\u0000insights and experimental results highlight that rider strategic behavior helps\u0000redistribute demand, reduce surge prices, and clear demand in a more balanced\u0000way across zones.","PeriodicalId":501316,"journal":{"name":"arXiv - CS - Computer Science and Game Theory","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Meta-mechanisms for Combinatorial Auctions over Social Networks 社交网络上组合拍卖的元机制

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-08 DOI: arxiv-2408.04555

Yuan Fang, Mengxiao Zhang, Jiamou Liu, Bakh Khoussainov

{"title":"Meta-mechanisms for Combinatorial Auctions over Social Networks","authors":"Yuan Fang, Mengxiao Zhang, Jiamou Liu, Bakh Khoussainov","doi":"arxiv-2408.04555","DOIUrl":"https://doi.org/arxiv-2408.04555","url":null,"abstract":"Recently there has been a large amount of research designing mechanisms for\u0000auction scenarios where the bidders are connected in a social network.\u0000Different from the existing studies in this field that focus on specific\u0000auction scenarios e.g. single-unit auction and multi-unit auction, this paper\u0000considers the following question: is it possible to design a scheme that, given\u0000a classical auction scenario and a mechanism $tilde{mathcal{M}}$ suited for\u0000it, produces a mechanism in the network setting that preserves the key\u0000properties of $tilde{mathcal{M}}$? To answer this question, we design\u0000meta-mechanisms that provide a uniform way of transforming mechanisms from\u0000classical models to mechanisms over networks and prove that the desirable\u0000properties are preserved by our meta-mechanisms. Our meta-mechanisms provide\u0000solutions to combinatorial auction scenarios in the network setting: (1)\u0000combinatorial auction with single-minded buyers and (2) combinatorial auction\u0000with general monotone valuation. To the best of our knowledge, this is the\u0000first work that designs combinatorial auctions over a social network.","PeriodicalId":501316,"journal":{"name":"arXiv - CS - Computer Science and Game Theory","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Balancing Efficiency with Equality: Auction Design with Group Fairness Concerns 平衡效率与平等：拍卖设计与群体公平问题

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-08 DOI: arxiv-2408.04545

Fengjuan Jia, Mengxiao Zhang, Jiamou Liu, Bakh Khoussainov

{"title":"Balancing Efficiency with Equality: Auction Design with Group Fairness Concerns","authors":"Fengjuan Jia, Mengxiao Zhang, Jiamou Liu, Bakh Khoussainov","doi":"arxiv-2408.04545","DOIUrl":"https://doi.org/arxiv-2408.04545","url":null,"abstract":"The issue of fairness in AI arises from discriminatory practices in\u0000applications like job recommendations and risk assessments, emphasising the\u0000need for algorithms that do not discriminate based on group characteristics.\u0000This concern is also pertinent to auctions, commonly used for resource\u0000allocation, which necessitate fairness considerations. Our study examines\u0000auctions with groups distinguished by specific attributes, seeking to (1)\u0000define a fairness notion that ensures equitable treatment for all, (2) identify\u0000mechanisms that adhere to this fairness while preserving incentive\u0000compatibility, and (3) explore the balance between fairness and seller's\u0000revenue. We introduce two fairness notions-group fairness and individual\u0000fairness-and propose two corresponding auction mechanisms: the Group\u0000Probability Mechanism, which meets group fairness and incentive criteria, and\u0000the Group Score Mechanism, which also encompasses individual fairness. Through\u0000experiments, we validate these mechanisms' effectiveness in promoting fairness\u0000and examine their implications for seller revenue.","PeriodicalId":501316,"journal":{"name":"arXiv - CS - Computer Science and Game Theory","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nash Equilibrium in Games on Graphs with Incomplete Preferences 不完全偏好图上博弈的纳什均衡

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-05 DOI: arxiv-2408.02860

Abhishek N. Kulkarni, Jie Fu, Ufuk Topcu

引用次数: 0

A Lower Bound for Local Search Proportional Approval Voting 本地搜索比例赞成票的下限

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-05 DOI: arxiv-2408.02300

Sonja Kraiczy, Edith Elkind

{"title":"A Lower Bound for Local Search Proportional Approval Voting","authors":"Sonja Kraiczy, Edith Elkind","doi":"arxiv-2408.02300","DOIUrl":"https://doi.org/arxiv-2408.02300","url":null,"abstract":"Selecting $k$ out of $m$ items based on the preferences of $n$ heterogeneous\u0000agents is a widely studied problem in algorithmic game theory. If agents have\u0000approval preferences over individual items and harmonic utility functions over\u0000bundles -- an agent receives $sum_{j=1}^tfrac{1}{j}$ utility if $t$ of her\u0000approved items are selected -- then welfare optimisation is captured by a\u0000voting rule known as Proportional Approval Voting (PAV). PAV also satisfies\u0000demanding fairness axioms. However, finding a winning set of items under PAV is\u0000NP-hard. In search of a tractable method with strong fairness guarantees, a\u0000bounded local search version of PAV was proposed by Aziz et al. It proceeds by\u0000starting with an arbitrary size-$k$ set $W$ and, at each step, checking if\u0000there is a pair of candidates $ain W$, $bnotin W$ such that swapping $a$ and\u0000$b$ increases the total welfare by at least $varepsilon$; if yes, it performs\u0000the swap. Aziz et al.~show that setting $varepsilon=frac{n}{k^2}$ ensures\u0000both the desired fairness guarantees and polynomial running time. However, they\u0000leave it open whether the algorithm converges in polynomial time if\u0000$varepsilon$ is very small (in particular, if we do not stop until there are\u0000no welfare-improving swaps). We resolve this open question, by showing that if\u0000$varepsilon$ can be arbitrarily small, the running time of this algorithm may\u0000be super-polynomial. Specifically, we prove a lower bound of~$Omega(k^{log\u0000k})$ if improvements are chosen lexicographically. To complement our lower\u0000bound, we provide an empirical comparison of two variants of local search --\u0000better-response and best-response -- on several real-life data sets and a\u0000variety of synthetic data sets. Our experiments indicate that, empirically,\u0000better response exhibits faster running time than best response.","PeriodicalId":501316,"journal":{"name":"arXiv - CS - Computer Science and Game Theory","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced Equilibria-Solving via Private Information Pre-Branch Structure in Adversarial Team Games 通过对抗性团队博弈中的私有信息预分支结构增强均衡解法

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-05 DOI: arxiv-2408.02283

Chen Qiu, Haobo Fu, Kai Li, Weixin Huang, Jiajia Zhang, Xuan Wang

{"title":"Enhanced Equilibria-Solving via Private Information Pre-Branch Structure in Adversarial Team Games","authors":"Chen Qiu, Haobo Fu, Kai Li, Weixin Huang, Jiajia Zhang, Xuan Wang","doi":"arxiv-2408.02283","DOIUrl":"https://doi.org/arxiv-2408.02283","url":null,"abstract":"In ex ante coordinated adversarial team games (ATGs), a team competes against\u0000an adversary, and the team members are only allowed to coordinate their\u0000strategies before the game starts. The team-maxmin equilibrium with correlation\u0000(TMECor) is a suitable solution concept for ATGs. One class of TMECor-solving\u0000methods transforms the problem into solving NE in two-player zero-sum games,\u0000leveraging well-established tools for the latter. However, existing methods are\u0000fundamentally action-based, resulting in poor generalizability and low solving\u0000efficiency due to the exponential growth in the size of the transformed game.\u0000To address the above issues, we propose an efficient game transformation method\u0000based on private information, where all team members are represented by a\u0000single coordinator. We designed a structure called private information\u0000pre-branch, which makes decisions considering all possible private information\u0000from teammates. We prove that the size of the game transformed by our method is\u0000exponentially reduced compared to the current state-of-the-art. Moreover, we\u0000demonstrate equilibria equivalence. Experimentally, our method achieves a\u0000significant speedup of 182.89$times$ to 694.44$times$ in scenarios where the\u0000current state-of-the-art method can work, such as small-scale Kuhn poker and\u0000Leduc poker. Furthermore, our method is applicable to larger games and those\u0000with dynamically changing private information, such as Goofspiel.","PeriodicalId":501316,"journal":{"name":"arXiv - CS - Computer Science and Game Theory","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Randomized Strategyproof Mechanisms with Best of Both Worlds Fairness and Efficiency 兼顾公平与效率的随机化策略防范机制

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-02 DOI: arxiv-2408.01027

Ankang Sun, Bo Chen

引用次数: 0

Game Theory Based Community-Aware Opinion Dynamics 基于博弈论的社区意识舆论动态

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-02 DOI: arxiv-2408.01196

Shanfan Zhang, Xiaoting Shen, Zhan Bu

{"title":"Game Theory Based Community-Aware Opinion Dynamics","authors":"Shanfan Zhang, Xiaoting Shen, Zhan Bu","doi":"arxiv-2408.01196","DOIUrl":"https://doi.org/arxiv-2408.01196","url":null,"abstract":"Examining the mechanisms underlying the formation and evolution of opinions\u0000within real-world social systems, which consist of numerous individuals, can\u0000provide valuable insights for effective social functioning and informed\u0000business decision making. The focus of our study is on the dynamics of opinions\u0000inside a networked multi-agent system. We provide a novel approach called the\u0000Game Theory Based Community-Aware Opinion Formation Process (GCAOFP) to\u0000accurately represent the co-evolutionary dynamics of communities and opinions\u0000in real-world social systems. The GCAOFP algorithm comprises two distinct steps\u0000in each iteration. 1) The Community Dynamics Process conceptualizes the process\u0000of community formation as a non-cooperative game involving a finite number of\u0000agents. Each individual agent aims to maximize their own utility by adopting a\u0000response that leads to the most favorable update of the community label. 2) The\u0000Opinion Formation Process involves the updating of an individual agent's\u0000opinion within a community-aware framework that incorporates bounded\u0000confidence. This process takes into account the updated matrix of community\u0000members and ensures that an agent's opinion aligns with the opinions of others\u0000within their community, within certain defined limits. The present study\u0000provides a theoretical proof that under any initial conditions, the\u0000aforementioned co-evolutionary dynamics process will ultimately reach an\u0000equilibrium state. In this state, both the opinion vector and community member\u0000matrix will stabilize after a finite number of iterations. In contrast to\u0000conventional opinion dynamics models, the guaranteed convergence of agent\u0000opinion within the same community ensures that the convergence of opinions\u0000takes place exclusively inside a given community.","PeriodicalId":501316,"journal":{"name":"arXiv - CS - Computer Science and Game Theory","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Game Theoretic Analysis of High Occupancy Toll Lane Design 高占用率收费车道设计的博弈论分析

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-02 DOI: arxiv-2408.01413

Zhanhao Zhang, Ruifan Yang, Manxi Wu

{"title":"A Game Theoretic Analysis of High Occupancy Toll Lane Design","authors":"Zhanhao Zhang, Ruifan Yang, Manxi Wu","doi":"arxiv-2408.01413","DOIUrl":"https://doi.org/arxiv-2408.01413","url":null,"abstract":"In this article, we study the optimal design of High Occupancy Toll (HOT)\u0000lanes. The traffic authority determines the road capacity allocation between\u0000HOT lanes and ordinary lanes, as well as the toll price charged for travelers\u0000using HOT lanes who do not meet the high-occupancy eligibility criteria. We\u0000develop a game-theoretic model to analyze the decisions of travelers with\u0000heterogeneous preference parameters in values of time and carpool disutilities.\u0000These travelers choose between paying or forming carpools to use the HOT lanes,\u0000or taking the ordinary lanes. Travelers' welfare depends on the congestion cost\u0000of the lane they use, the toll payment, and the carpool disutilities. For\u0000highways with a single entrance and exit node, we provide a complete\u0000characterization of equilibrium strategies and a comparative statics analysis\u0000of how the equilibrium vehicle flow and travel time change with HOT capacity\u0000and toll price. We then extend the single segment model to highways with\u0000multiple entrance and exit nodes. We extend the equilibrium concept and propose\u0000various design objectives considering traffic congestion, toll revenue, and\u0000social welfare. Using the data collected from the HOT lane of the California\u0000Interstate Highway 880 (I-880), we formulate a convex program to estimate the\u0000travel demand and approximate the distribution of travelers' preference\u0000parameters. We then compute the optimal toll design of five segments for I-880\u0000for achieve each one of the four objectives, and compare the optimal solution\u0000with the current toll pricing.","PeriodicalId":501316,"journal":{"name":"arXiv - CS - Computer Science and Game Theory","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trustworthy Machine Learning under Social and Adversarial Data Sources 社交和对抗性数据源下值得信赖的机器学习

arXiv - CS - Computer Science and Game Theory Pub Date : 2024-08-02 DOI: arxiv-2408.01596

Han Shao

引用次数: 0