Theoretical Computer Science最新文献_第5页

The min-move mutual visibility problem for disoriented asynchronous robots

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-18 DOI: 10.1016/j.tcs.2025.115125

Subhash Bhagat , Krishnendu Mukhopadhyaya , Rajarshi Ray

{"title":"The min-move mutual visibility problem for disoriented asynchronous robots","authors":"Subhash Bhagat , Krishnendu Mukhopadhyaya , Rajarshi Ray","doi":"10.1016/j.tcs.2025.115125","DOIUrl":"10.1016/j.tcs.2025.115125","url":null,"abstract":"<div><div>We consider a distributed system of <span><math><mi>n</mi><mo>≥</mo><mn>3</mn></math></span> autonomous robots in the Euclidean plane under the <em>obstructed visibility model</em>. In the <em>obstructed visibility model</em>, robots are considered opaque, and if three robots lie on a straight line, the mid- dle robot blocks the vision of the two other robots. The <em>mutual visibility problem</em> requires the robots to coordinate their movements in such a way that all the robots in the system become mutually visible. This paper studies a constrained version of the mutual visibility problem, namely the <em>min-move mutual visibility problem</em>. The min-move mutual visibility problem asks to solve the mutual visibility problem by moving each robot at most once. One of the major implications of this constrained version of the mutual visibility problem is that it also addresses the issue of energy efficiency for the robots. We study the min-move mutual visibility problem for disoriented robots (i.e., robots not having any form of local axis agreement or common chirality). We study the problem under two of the strongest adversarial models, namely asynchronous scheduler and non- rigid movements. We first show that the min-move mutual visibility problem is not solvable for disoriented asynchronous robots with non-rigid movements in the absence of externally visible lights. Then, we analyze different characteristics of a min-move mutual visibility algorithm for disoriented robots with non-rigid movements. We use these properties to present a distributed algorithm that solves the problem for disoriented asynchronous robots with non-rigid movements and having externally visible lights (FALL light model). The algorithm uses only 7 colors for the lights. The proposed algorithm is collision-free and runs in <span><math><mi>O</mi><mo>(</mo><mi>n</mi><mo>)</mo></math></span> epochs.</div></div>","PeriodicalId":49438,"journal":{"name":"Theoretical Computer Science","volume":"1035 ","pages":"Article 115125"},"PeriodicalIF":0.9,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

For rational numbers with Suppes-Ono division, equational validity is one-one equivalent with Diophantine unsolvability

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-17 DOI: 10.1016/j.tcs.2025.115124

Jan A. Bergstra , John V. Tucker

引用次数: 0

Fast and simple (1 + ε)Δ-edge-coloring of dense graphs

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-17 DOI: 10.1016/j.tcs.2025.115126

Abhishek Dhawan

引用次数: 0

Network control games played on graphs

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-13 DOI: 10.1016/j.tcs.2025.115123

Zihui Liang, Bakh Khoussainov, Mingyu Xiao

引用次数: 0

A note on quantum divide and conquer for minimal string rotation

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-12 DOI: 10.1016/j.tcs.2025.115120

Qisheng Wang

引用次数: 0

Lower bounds for graph reconstruction with maximal independent set queries

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-11 DOI: 10.1016/j.tcs.2025.115121

Lukas Michel, Alex Scott

{"title":"Lower bounds for graph reconstruction with maximal independent set queries","authors":"Lukas Michel, Alex Scott","doi":"10.1016/j.tcs.2025.115121","DOIUrl":"10.1016/j.tcs.2025.115121","url":null,"abstract":"<div><div>We investigate the number of maximal independent set queries required to reconstruct the edges of a hidden graph. We show that randomised adaptive algorithms need at least <span><math><mi>Ω</mi><mo>(</mo><msup><mrow><mi>Δ</mi></mrow><mrow><mn>2</mn></mrow></msup><mi>log</mi><mo>⁡</mo><mo>(</mo><mi>n</mi><mo>/</mo><mi>Δ</mi><mo>)</mo><mo>/</mo><mi>log</mi><mo>⁡</mo><mi>Δ</mi><mo>)</mo></math></span> queries to reconstruct <em>n</em>-vertex graphs of maximum degree Δ with success probability at least 1/2, and we further improve this lower bound to <span><math><mi>Ω</mi><mo>(</mo><msup><mrow><mi>Δ</mi></mrow><mrow><mn>2</mn></mrow></msup><mi>log</mi><mo>⁡</mo><mo>(</mo><mi>n</mi><mo>/</mo><mi>Δ</mi><mo>)</mo><mo>)</mo></math></span> for randomised non-adaptive algorithms. We also prove that deterministic non-adaptive algorithms require at least <span><math><mi>Ω</mi><mo>(</mo><msup><mrow><mi>Δ</mi></mrow><mrow><mn>3</mn></mrow></msup><mi>log</mi><mo>⁡</mo><mi>n</mi><mo>/</mo><mi>log</mi><mo>⁡</mo><mi>Δ</mi><mo>)</mo></math></span> queries.</div><div>This improves bounds of Konrad, O'Sullivan, and Traistaru, and answers one of their questions. The proof of the lower bound for deterministic non-adaptive algorithms relies on a connection to cover-free families, for which we also improve known bounds.</div></div>","PeriodicalId":49438,"journal":{"name":"Theoretical Computer Science","volume":"1034 ","pages":"Article 115121"},"PeriodicalIF":0.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Shell sort with expected complexity of O(nlog2n) 壳排序的预期复杂度为 O(nlog2n)

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-11 DOI: 10.1016/j.tcs.2025.115122

Shengrong Hu

引用次数: 0

Unpaired set-to-set disjoint path routings in recursive match networks

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-10 DOI: 10.1016/j.tcs.2025.115111

Bai Yin , Qianru Zhou , Hai Liu , Yan Wang , Baolei Cheng , Jianxi Fan

引用次数: 0

Optimizing resource allocation: An active learning approach to iterative combinatorial auctions

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-04 DOI: 10.1016/j.tcs.2025.115104

Benjamin Estermann , Stefan Kramer , Roger Wattenhofer , Kanye Ye Wang

{"title":"Optimizing resource allocation: An active learning approach to iterative combinatorial auctions","authors":"Benjamin Estermann , Stefan Kramer , Roger Wattenhofer , Kanye Ye Wang","doi":"10.1016/j.tcs.2025.115104","DOIUrl":"10.1016/j.tcs.2025.115104","url":null,"abstract":"<div><div>In deep learning-based iterative combinatorial auctions (DL-ICA), bidders are not required to report valuations for all bundles upfront. Instead, DL-ICA iteratively requests bidders to report their values for specific bundles and determines item allocation using a winner determination problem, with bidder profiles modeled by neural networks. However, due to the limited number of reported bundles, DL-ICA may not always achieve optimal winner allocation, leading to reduced economic efficiency. In this work, we enhance the economic efficiency, specifically the social welfare, of DL-ICA by optimizing the underlying machine learning-based elicitation algorithm. We introduce two novel active learning-based initial sampling strategies: GALI and GALO. GALI ensures optimal coverage of the entire bundle space during sampling, while GALO identifies bundles with high diversity in bidders' estimated values as determined by the neural network. This approach extends the application of active learning beyond small pool sizes. We demonstrate how linear programs can be utilized for active learning to manage pool sizes exceeding 10<sup>30</sup> samples. Our approach is theoretically validated and experimentally verified, showcasing significant improvements in performance.</div></div>","PeriodicalId":49438,"journal":{"name":"Theoretical Computer Science","volume":"1033 ","pages":"Article 115104"},"PeriodicalIF":0.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Opinion maximization in social networks via link recommendation

IF 0.9 4区计算机科学

Theoretical Computer Science Pub Date : 2025-02-03 DOI: 10.1016/j.tcs.2025.115090

Liwang Zhu , Zhongzhi Zhang

{"title":"Opinion maximization in social networks via link recommendation","authors":"Liwang Zhu , Zhongzhi Zhang","doi":"10.1016/j.tcs.2025.115090","DOIUrl":"10.1016/j.tcs.2025.115090","url":null,"abstract":"<div><div>We study a variation of the Friedkin-Johnsen model for opinion dynamics in a leader-follower social network with <em>n</em> nodes and <em>m</em> edges, where the node set is partitioned into three subsets: set of leader nodes with opinion 1, set of leaders with opinion 0, and set of follower nodes. We give an explicit expression for the steady-state opinion vector in terms of some related matrices and the initial opinion vector, and interpret the equilibrium opinion vector as the weighted average of the initial opinions for all nodes with the weights being the escape probabilities of a defining random walk. We then pose an opinion maximization problem of recommending <em>k</em> new edges between 1-leader and follower nodes so that the equilibrium overall opinion is maximized. We show that the objective function is monotone and submodular, and propose a simple greedy algorithm with an approximation factor <span><math><mo>(</mo><mn>1</mn><mo>−</mo><mfrac><mrow><mn>1</mn></mrow><mrow><mi>e</mi></mrow></mfrac><mo>)</mo></math></span> that approximately solves the problem in cubic running time. To speed up the computation, we also provide a fast algorithm with an approximation ratio <span><math><mo>(</mo><mn>1</mn><mo>−</mo><mfrac><mrow><mn>1</mn></mrow><mrow><mi>e</mi></mrow></mfrac><mo>−</mo><mi>ϵ</mi><mo>)</mo></math></span> and computation complexity <span><math><mover><mrow><mi>O</mi></mrow><mrow><mo>˜</mo></mrow></mover><mo>(</mo><mi>m</mi><mi>k</mi><msup><mrow><mi>ϵ</mi></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup><mo>)</mo></math></span> for any <span><math><mi>ϵ</mi><mo>></mo><mn>0</mn></math></span>, where the <span><math><mover><mrow><mi>O</mi></mrow><mrow><mo>˜</mo></mrow></mover><mo>(</mo><mo>⋅</mo><mo>)</mo></math></span> notation suppresses the <span><math><mrow><mi>poly</mi></mrow><mo>(</mo><mi>log</mi><mo>⁡</mo><mi>n</mi><mo>)</mo></math></span> factors. Extensive experiments on both real social networks with real opinions and datasets with synthetic opinions demonstrate that our algorithms are effective, efficient, and scale well to large social networks.</div></div>","PeriodicalId":49438,"journal":{"name":"Theoretical Computer Science","volume":"1033 ","pages":"Article 115090"},"PeriodicalIF":0.9,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0