Zobrazeno 1 - 10
of 389
pro vyhledávání: '"Koenig, Sven"'
Anytime multi-agent path finding (MAPF) is a promising approach to scalable path optimization in multi-agent systems. MAPF-LNS, based on Large Neighborhood Search (LNS), is the current state-of-the-art approach where a fast initial solution is iterat
Externí odkaz:
http://arxiv.org/abs/2408.02960
In this past year, large language models (LLMs) have had remarkable success in domains outside the traditional natural language processing, and people are starting to explore the usage of LLMs in more general and close to application domains like cod
Externí odkaz:
http://arxiv.org/abs/2406.11132
ITA-ECBS: A Bounded-Suboptimal Algorithm for the Combined Target-Assignment and Path-Finding Problem
Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, plays a critical role in many applications. Sometimes, assigning a target to each agent also presents a challenge. The Combined Target-Assignment and Path-Findin
Externí odkaz:
http://arxiv.org/abs/2404.05223
Since more and more algorithms are proposed for multi-agent path finding (MAPF) and each of them has its strengths, choosing the correct one for a specific scenario that fulfills some specified requirements is an important task. Previous research in
Externí odkaz:
http://arxiv.org/abs/2404.03554
Cooperative multi-agent reinforcement learning (MARL) has been an increasingly important research topic in the last half-decade because of its great potential for real-world applications. Because of the curse of dimensionality, the popular "centraliz
Externí odkaz:
http://arxiv.org/abs/2404.03101
Multi-Agent Path Finding (MAPF), which involves finding collision-free paths for multiple robots, is crucial in various applications. Lifelong MAPF, where targets are reassigned to agents as soon as they complete their initial targets, offers a more
Externí odkaz:
http://arxiv.org/abs/2403.13421
Autor:
Chan, Shao-Hung, Chen, Zhe, Lin, Dian-Lun, Zhang, Yue, Harabor, Daniel, Huang, Tsung-Wei, Koenig, Sven, Phan, Thomy
Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths for multiple agents in a shared environment while minimizing the sum of travel time. Since solving the MAPF problem optimally is NP-hard, anytime algorithms based
Externí odkaz:
http://arxiv.org/abs/2402.01961
A wide range of real-world applications can be formulated as Multi-Agent Path Finding (MAPF) problem, where the goal is to find collision-free paths for multiple agents with individual start and goal locations. State-of-the-art MAPF solvers are mainl
Externí odkaz:
http://arxiv.org/abs/2401.05860
With the explosive influence caused by the success of large language models (LLM) like ChatGPT and GPT-4, there has been an extensive amount of recent work showing that foundation models can be used to solve a large variety of tasks. However, there i
Externí odkaz:
http://arxiv.org/abs/2401.03630
Anytime multi-agent path finding (MAPF) is a promising approach to scalable path optimization in large-scale multi-agent systems. State-of-the-art anytime MAPF is based on Large Neighborhood Search (LNS), where a fast initial solution is iteratively
Externí odkaz:
http://arxiv.org/abs/2312.16767