Test data for Map 3.

Test data for Map 3.

<div><p>An effective Multi-Agent Path Finding (MAPF) algorithm must efficiently plan paths for multiple agents while adhering to constraints, ensuring safe navigation from start to goal. However, due to partial observability, agents often struggle to determine optimal strategies. Thus, d...

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Bibliographic Details
Main Author: Qingling Zhang (758713) (author)
Other Authors: Peng Wang (34436) (author), Cui Ni (14773398) (author), Xianchang Liu (11260136) (author)
Published: 2025
Subjects:
Neuroscience
Biotechnology
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
varying map sizes
spatial dimensions based
predicting future actions
graph attention networks
gated recurrent unit
final action strategy
experimental results show
ensuring safe navigation
determine optimal strategies
convolutional neural network
algorithm &# 8217
5 %, 73
agents often struggle
agent path finding
agent &# 8217
partial observability problem
information fusion expands
partial observability
multiple agents
fusion approach
agent densities
agent communication
xlink ">
time efficiency
thereby enhancing
scaled dot
product aggregation
performance enhancement
paper explores
overall performance
observation range
larger maps
historical observations
enable inter
effectively solving
effective multi
continuous task
aggregated data
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