arXiv subjects

Takahiro Suzuki

Publications and source records attributed to Takahiro Suzuki.

At least 19 recordsLinked to original sources

arXiv2026

Finding Shortest Reconfiguration Sequences on Independent Set Polytopes

We initiate the study of the shortest reconfiguration problem for independent sets under the adjacency relation derived from the independent set polytope. Given a graph and two independent sets, the problem asks for a shortest sequence transforming one into the other such that the subgraph induced by the symmetric difference of any two consecutive sets is connected. This is equivalent to finding a shortest path on the $1$-skeleton of the independent set polytope. We prove that the problem is NP-hard even on planar graphs of bounded degree, as well as on split graphs. Notably, the hardness for planar graphs of bounded degree still holds even when deciding whether the target can be reached in at most two steps. For split graphs, we further show the W[2]-hardness when parameterized by the number of steps, as well as the inapproximability of the optimal length. As a consequence, we prove that the length of a shortest path between two vertices of a 0/1 polytope in $\mathbb{R}^n$ described by $O(n)$ linear inequalities is hard to approximate within a factor of $(1-\varepsilon)\ln n$ for any constant $ε>0$, unless $P=NP$. On the positive side, we provide polynomial-time algorithms for block graphs, cographs, and bipartite chain graphs. Moreover, for paths and cycles, we show that the optimal length of the shortest reconfiguration sequence exactly matches a trivial upper bound.

cs.DS↗

arXiv2026

Distance-Constrained Unlabeled Multi-Agent Pathfinding

We study a graph pathfinding problem Distance-$r$ Independent Unlabeled Multi-Agent Pathfinding, finding a set of collision-free paths between two sets where agents must stay at pairwise distance at least $r+1$ at all times. This additional constraint, generalizing collision modeling for classical MAPF, targets aspects of real-world multi-agent coordination. This additional distance constraint makes feasibility (i.e., whether a solution exists) PSPACE-complete, in contrast to standard (unlabeled) MAPF, where it can be decided in polynomial time. We address the challenge via two complementary approaches: (i) reduction-based optimal algorithms with a feasibility-preserving compression procedure, and (ii) a configuration generator-based search. Despite the hardness, empirical results show that our algorithm can handle hundreds of agents in a practical timeframe.

cs.MA↗

arXiv2026

Parameterized Complexity of Odd Domination and its Generalization

In the \textsc{Odd Domination} problem, given a graph $G$ and a positive integer $k$, the task is to determine whether there exists a vertex subset $D$ of $G$ such that the closed neighborhood of each vertex in $G$ contains an odd number of vertices from $D$. In this paper, we investigate the computational complexity of the problem. When parameterized by the solution size $k$, we establish W[1]-hardness on some restricted graphs and a sharp boundary between fixed-parameter tractability and W[1]-hardness with respect to the girth of the input graph. Then, we address the problem when parameterized by several structural graph parameters. Furthermore, we investigate the parameterized complexity of \textsc{Parity Domination}, which is a generalization of \textsc{Odd Domination}.

cs.DS↗

arXiv2026

Consistency, unanimity, and the Borda rule in social ranking

The social ranking is a recently proposed framework for evaluating the power of individuals according to the performance ranking of their coalitions. Although its origin can be traced to the classical power indices in simple games, social ranking approaches carry out this evaluation within the ordinal framework of social choice theory. This article introduces the Borda rule into social ranking. Specifically, we focus on two essential properties of the Borda rule--consistency and closeness to unanimity--and investigate the social ranking solutions (SRSs) satisfying these properties. Among several possible definitions of the Borda rule as an SRS, we characterize one of such solutions by (a weak version of) consistency, closeness to unanimity (under the linear and symmetric domain), neutrality (i.e., names of the individuals do not matter), and independence of perfunctory participation (i.e., adding a perfunctory coalition into the worst class of the coalitional ranking does not affect the social ranking). We therefore propose a new Borda-type SRS for evaluating the competence of individuals in coalitional contexts.

econ.TH↗

arXiv2026

Consistencies in Social Ranking

Ranking individuals based on their performance in different coalitions is a problem emerging in various domains (teams sports, scientific evaluation, argumentation, etc.). Often, for practical reasons, the number of comparable coalitions is limited. Therefore, the foundational principles of ranking solutions must support realistic interpretations in contexts where only certain coalitions can be compared. To address this issue, in this paper we present an axiomatic analysis of solutions for the social ranking problem centered on the notion of consistency. More precisely, we show that an appropriate notion of consistency, which specifies how to combine rankings on individuals across different rankings on coalitions, plays a key role in any axiomatic characterization, representing the true distinguishing feature of each solution. This role is further highlighted by the taxonomy of the complementary axioms used in our characterizations, which boil down to well-studied properties of invariance with respect to the label of players or coalitions, and also with respect to minor changes in a coalitional ranking. By showing the logical independence of the axioms used in each characterization, as well as a rigorous analysis of alternative notions of consistency with respect to the majority of solutions from the literature, this work attempts to provide a first systematic study of the social ranking problem over a variable domain of coalitions.

econ.TH↗

arXiv2026

Polynomial-time Configuration Generator for Connected Unlabeled Multi-Agent Pathfinding

We consider Connected Unlabeled Multi-Agent Pathfinding (CUMAPF), a variant of MAPF where interchangeable agents must be connected at all times. This problem is fundamental to swarm robotics applications such as self-reconfiguration and marching, where standard MAPF is insufficient as it does not guarantee the connectivity constraint. Despite its simple structure, CUMAPF remains understudied and lacks practical algorithms. We first develop an Integer Linear Programming (ILP) reduction to solve CUMAPF. Although this formulation provides a makespan-optimal plan, it is severely limited in terms of scalability and real-time responsiveness due to the large number of variables. We therefore propose a suboptimal but complete algorithm named PULL. It is based on a rule-based one-step function that computes a subsequent configuration that preserves connectivity and advances towards the target configuration. PULL is lightweight, and runs in $O(n^2)$ time per step in a 2D grid, where $n$ is the number of agents. Empirically, PULL can quickly solve randomly generated instances containing hundreds of agents, which ILP cannot handle. Furthermore, PULL's solution substantially improves upon a naive approach to CUMAPF.

cs.MA↗

arXiv2026

Fabrication of high-Q defect-free optical nanofiber photonic crystal resonators

We demonstrate the fabrication of defect-free optical-nanofiber photonic-crystal Fabry-Perot resonators with quality factors exceeding 10^7 using single-shot femtosecond laser ablation. An investigation of the nonlinear optical properties reveals that thermo-optic effects dominate within the entire cavity bandwidth, even when interrogating with pulses one order of magnitude shorter than the 6.6 us thermal cutoff time. The combination of high-Q and small mode volume of these resonators could facilitate the creation of high-speed quantum nodes for cavity QED based quantum computing and networking, as well as low-power in-line fiber optical switches.

physics.optics↗

arXiv2025

Spanning Trees with a Small Vertex Cover: the Complexity on Specific Graph Classes

In the context of algorithm theory, various studies have been conducted on spanning trees with desirable properties. In this paper, we consider the \textsc{Minimum Cover Spanning Tree} problem (MCST for short). Given a graph $G$ and a positive integer $k$, the problem determines whether $G$ has a spanning tree with a vertex cover of size at most $k$. We reveal the equivalence between \mcst\ and the \textsc{Dominating Set} problem when $G$ is of diameter at most~$2$ or $P_5$-free. This provides the intractability for these graphs and the tractability for several subclasses of $P_5$-free graphs. We also show that \mcst\ is NP-complete for bipartite planar graphs of maximum degree~$4$ and unit disk graphs. These hardness results resolve open questions posed in prior research. Finally, we present an FPT algorithm for {\mcst} parameterized by clique-width and a linear-time algorithm for interval graphs.

cs.DS↗

arXiv2025

Solution Discovery for Vertex Cover, Independent Set, Dominating Set, and Feedback Vertex Set

In the solution discovery problem for a search problem on graphs, we are given an initial placement of $k$ tokens on the vertices of a graph and asked whether this placement can be transformed into a feasible solution by applying a small number of modifications. In this paper, we study the computational complexity of solution discovery for several fundamental vertex-subset problems on graphs, namely Vertex Cover Discovery, Independent Set Discovery, Dominating Set Discovery, and Feedback Vertex Set Discovery. We first present XP algorithms for all four problems parameterized by clique-width. We then prove that Vertex Cover Discovery, Independent Set Discovery, and Feedback Vertex Set Discovery are NP-complete for chordal graphs and graphs of diameter 2, which have unbounded clique-width. In contrast to these hardness results, we show that all three problems can be solved in polynomial time on split graphs. Furthermore, we design an FPT algorithm for Feedback Vertex Set Discovery parameterized by the number of tokens.

cs.DS↗

arXiv2025

Coloring Reconfiguration under Color Swapping

In the \textsc{Coloring Reconfiguration} problem, we are given two proper $k$-colorings of a graph and asked to decide whether one can be transformed into the other by repeatedly applying a specified recoloring rule, while maintaining a proper coloring throughout. For this problem, two recoloring rules have been widely studied: \emph{single-vertex recoloring} and \emph{Kempe chain recoloring}. In this paper, we introduce a new rule, called \emph{color swapping}, where two adjacent vertices may exchange their colors, so that the resulting coloring remains proper, and study the computational complexity of the problem under this rule. We first establish a complexity dichotomy with respect to $k$: the problem is solvable in polynomial time for $k \leq 2$, and is PSPACE-complete for $k \geq 3$. We further show that the problem remains PSPACE-complete even on restricted graph classes, including bipartite graphs, split graphs, and planar graphs of bounded degree. In contrast, we present polynomial-time algorithms for several graph classes: for paths when $k = 3$, for split graphs when $k$ is fixed, and for cographs when $k$ is arbitrary.

cs.DS↗

arXiv2025

Independence Axioms in Social Ranking

Independence from non-essential changes in input information is a widely recognized axiom in social choice theory. This independence reduces the cost of specifying and/or analyzing non-essential data. This study makes a comprehensive analysis of independence axioms in the context of social ranking solutions (SRSs). We consider seven independence axioms (two of which are new) and provide a novel characterization of the lexicographic excellence solution and plurality by substituting these independence axioms in the existing characterization of the intersection initial segment rule. The characterizations highlight the differences among the three SRSs in terms of independence.

econ.TH↗

arXiv2025

Automatic Operation of an Articulated Dump Truck: State Estimation by Combined QZSS CLAS and Moving-Base RTK Using Multiple GNSS Receivers

Labor shortage due to the declining birth rate has become a serious problem in the construction industry, and automation of construction work is attracting attention as a solution to this problem. This paper proposes a method to realize state estimation of dump truck position, orientation and articulation angle using multiple GNSS for automatic operation of dump trucks. RTK-GNSS is commonly used for automation of construction equipment, but in mountainous areas, mobile networks often unstable, and RTK-GNSS using GNSS reference stations cannot be used. Therefore, this paper develops a state estimation method for dump trucks that does not require a GNSS reference station by using the Centimeter Level Augmentation Service (CLAS) of the Japanese Quasi-Zenith Satellite System (QZSS). Although CLAS is capable of centimeter-level position estimation, its positioning accuracy and ambiguity fix rate are lower than those of RTK-GNSS. To solve this problem, we construct a state estimation method by factor graph optimization that combines CLAS positioning and moving-base RTK-GNSS between multiple GNSS antennas. Evaluation tests under real-world environments have shown that the proposed method can estimate the state of dump trucks with the same accuracy as conventional RTK-GNSS, but does not require a GNSS reference station.

cs.RO↗

arXiv2025

Mill's canons meet social ranking: A characterization of plurality

In his book entitled ''A System of Logic, Ratiocinative and Inductive'' (1843), John Stuart Mill proposed principles of inductive reasoning in the form of five canons. To date, these canons are classic methods for causal reasoning: they are intended to single out the circumstances that are connected to the phenomenon under focus. The present paper reinterprets Mill's canons in the modern theory of social ranking solutions, which aims to estimate the power of individuals based on teams' performances. We first apply Mill's canons to determine the key success factors in cooperative performances and then characterize plurality using a strong version of Mill's first canon. Plurality is also compatible with most other canons. Thus, our results demonstrated a hidden link between classical causal reasoning and the theory of social ranking solutions.

econ.TH↗

arXiv2025

Ranking alternatives from opinions on criteria

A primary challenge in collective decision-making is that achieving unanimous agreement is difficult, even at the level of criteria. The history of social choice theory illustrates this: numerous normative criteria on voting rules have been proposed; however, disagreements persist regarding which criteria should take precedence. This study addresses the problem of ranking alternatives based on the aggregation of opinions over criteria that the alternatives might fulfill. Using the opinion aggregation model, we propose a new rule, termed the Intersection Initial Segment (IIS) rule, and characterize it using five axioms: neutrality, independence of the worst set, independence of the best set, weak intersection very important player, and independence of non-unanimous improvement. We illustrate our approach on a running example where the objective is to rank voting rules, showing that our opinion aggregation model is particularly well-suited to this context, and that the IIS rule is a counterpart to the method discussed in Nurmi's paper (2015).

econ.TH↗

arXiv2023

Estimation of articulated angle in six-wheeled dump trucks using multiple GNSS receivers for autonomous driving

Due to the declining birthrate and aging population, the shortage of labor in the construction industry has become a serious problem, and increasing attention has been paid to automation of construction equipment. We focus on the automatic operation of articulated six-wheel dump trucks at construction sites. For the automatic operation of the dump trucks, it is important to estimate the position and the articulated angle of the dump trucks with high accuracy. In this study, we propose a method for estimating the state of a dump truck by using four global navigation satellite systems (GNSSs) installed on an articulated dump truck and a graph optimization method that utilizes the redundancy of multiple GNSSs. By adding real-time kinematic (RTK)-GNSS constraints and geometric constraints between the four antennas, the proposed method can robustly estimate the position and articulation angle even in environments where GNSS satellites are partially blocked. As a result of evaluating the accuracy of the proposed method through field tests, it was confirmed that the articulated angle could be estimated with an accuracy of 0.1$^\circ$ in an open-sky environment and 0.7$^\circ$ in a mountainous area simulating an elevation angle of 45$^\circ$ where GNSS satellites are blocked.

cs.RO↗

arXiv2022

Goldilocks-curriculum Domain Randomization and Fractal Perlin Noise with Application to Sim2Real Pneumonia Lesion Detection

A computer-aided detection (CAD) system based on machine learning is expected to assist radiologists in making a diagnosis. It is desirable to build CAD systems for the various types of diseases accumulating daily in a hospital. An obstacle in developing a CAD system for a disease is that the number of medical images is typically too small to improve the performance of the machine learning model. In this paper, we aim to explore ways to address this problem through a sim2real transfer approach in medical image fields. To build a platform to evaluate the performance of sim2real transfer methods in the field of medical imaging, we construct a benchmark dataset that consists of $101$ chest X-images with difficult-to-identify pneumonia lesions judged by an experienced radiologist and a simulator based on fractal Perlin noise and the X-ray principle for generating pseudo pneumonia lesions. We then develop a novel domain randomization method, called Goldilocks-curriculum domain randomization (GDR) and evaluate our method in this platform.

cs.CV↗

arXiv2020

Black-box Adversarial Attacks on Monocular Depth Estimation Using Evolutionary Multi-objective Optimization

This paper proposes an adversarial attack method to deep neural networks (DNNs) for monocular depth estimation, i.e., estimating the depth from a single image. Single image depth estimation has improved drastically in recent years due to the development of DNNs. However, vulnerabilities of DNNs for image classification have been revealed by adversarial attacks, and DNNs for monocular depth estimation could contain similar vulnerabilities. Therefore, research on vulnerabilities of DNNs for monocular depth estimation has spread rapidly, but many of them assume white-box conditions where inside information of DNNs is available, or are transferability-based black-box attacks that require a substitute DNN model and a training dataset. Utilizing Evolutionary Multi-objective Optimization, the proposed method in this paper analyzes DNNs under the black-box condition where only output depth maps are available. In addition, the proposed method does not require a substitute DNN that has a similar architecture to the target DNN nor any knowledge about training data used to train the target model. Experimental results showed that the proposed method succeeded in attacking two DNN-based methods that were trained with indoor and outdoor scenes respectively.

cs.CV↗

arXiv2019

Adversarial Example Generation using Evolutionary Multi-objective Optimization

This paper proposes Evolutionary Multi-objective Optimization (EMO)-based Adversarial Example (AE) design method that performs under black-box setting. Previous gradient-based methods produce AEs by changing all pixels of a target image, while previous EC-based method changes small number of pixels to produce AEs. Thanks to EMO's property of population based-search, the proposed method produces various types of AEs involving ones locating between AEs generated by the previous two approaches, which helps to know the characteristics of a target model or to know unknown attack patterns. Experimental results showed the potential of the proposed method, e.g., it can generate robust AEs and, with the aid of DCT-based perturbation pattern generation, AEs for high resolution images.

cs.CV↗