Zobrazeno 1 - 10
of 40 865
pro vyhledávání: '"Pathfinding"'
The Lightning Network is a peer-to-peer network designed to address Bitcoin's scalability challenges, facilitating rapid, cost-effective, and instantaneous transactions through bidirectional, blockchain-backed payment channels among network peers. Du
Externí odkaz:
http://arxiv.org/abs/2410.13784
This paper introduces a novel approach to urban pathfinding by transforming traditional heuristic-based algorithms into deep learning models that leverage real-time contextual data, such as traffic and weather conditions. We propose two methods: an e
Externí odkaz:
http://arxiv.org/abs/2411.05044
Autor:
Ono, Masahiro
Advancements in cytometry technologies have led to a remarkable increase in the number of markers that can be analyzed simultaneously, presenting significant challenges in data analysis. Traditional approaches, such as dimensional reduction technique
Externí odkaz:
http://arxiv.org/abs/2411.00129
Autor:
Pertzovsky, Arseniy
In this paper, we solve the classical Multi-agent Pathfinding (MAPF) problem. Existing approaches struggle to solve dense MAPF instances. In this paper, we propose a Corridor Generating Algorithm for MAPF, namely CGA-MAPF. In CGA-MAPF, the agents bui
Externí odkaz:
http://arxiv.org/abs/2410.12397
Autor:
Yan, Zhen, Shen, Zhiqiang, Jiang, Peng, Zhang, Bo, Zhang, Haiyan, Cui, Lang, Luo, Jintao, Chen, Rurong, Jiang, Wu, Zhang, Hua, Wu, De, Zhao, Rongbing, Yuan, Jianping, Hu, Yue, Wu, Yajun, Xia, Bo, Li, Guanghui, Rao, Yongnan, Chen, Chenyu, Wang, Xiaowei, Ding, Hao, Liu, Yongpeng, Zhang, Fuchen, Jiang, Yongbin
The importance of Very Long Baseline Interferometry (VLBI) for pulsar research is becoming increasingly prominent and receiving more and more attention. In this paper, we present pathfinding pulsar observation results with the Chinese VLBI Network (C
Externí odkaz:
http://arxiv.org/abs/2409.16059
Autor:
Vallarino, Diego
This paper introduces a novel approach to optimizing portfolio rebalancing by integrating Graph Neural Networks (GNNs) for predicting transaction costs and Dijkstra's algorithm for identifying cost-efficient rebalancing paths. Using historical stock
Externí odkaz:
http://arxiv.org/abs/2410.01864
Autor:
Okumura, Keisuke
We study a pathfinding problem where only locations (i.e., vertices) are given, and edges are implicitly defined by an oracle answering the connectivity of two locations. Despite its simple structure, this problem becomes non-trivial with a massive n
Externí odkaz:
http://arxiv.org/abs/2408.15443
In this paper we study a challenging variant of the multi-agent pathfinding problem (MAPF), when a set of agents must reach a set of goal locations, but it does not matter which agent reaches a specific goal - Anonymous MAPF (AMAPF). Current optimal
Externí odkaz:
http://arxiv.org/abs/2408.14948
Autor:
Li, Jianqiang, Tong, Yu
Finding problems that allow for superpolynomial quantum speedup is one of the most important tasks in quantum computation. A key challenge is identifying problem structures that can only be exploited by quantum mechanics. In this paper, we find a cla
Externí odkaz:
http://arxiv.org/abs/2407.14398
Pathfinding problems are found throughout robotics, computational science, and natural sciences. Traditional methods to solve these require training deep neural networks (DNNs) for each new problem domain, consuming substantial time and resources. Th
Externí odkaz:
http://arxiv.org/abs/2406.02598