A systematic literature review of multi-agent pathfinding for maze research
Multi-agent Pathfinding, also known as MAPF, is an Artificial Intelligence problem-solving. The aim is to direct each agent to find its path to reach its target, both individually and in groups. Of course, this path allows agents to move without colliding with each other. This MAPF applica...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Academy Publisher
2022
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| Online Access: | http://eprints.utem.edu.my/id/eprint/27074/2/017260604202355.PDF http://eprints.utem.edu.my/id/eprint/27074/ https://www.jait.us/index.php?m=content&c=index&a=show&catid=220&id=1240 |
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| Summary: | Multi-agent Pathfinding, also known as MAPF, is
an Artificial Intelligence problem-solving. The aim is to
direct each agent to find its path to reach its target, both
individually and in groups. Of course, this path allows agents
to move without colliding with each other. This MAPF
application is implemented in many areas that require the
movement of various agents, such as warehouse robots,
autonomous cars, video games, traffic control, Unmanned
Aerial Vehicles (UAV), Search and Rescue (SAR), many
others. The use of multi-agent in exploring often assumes all
areas to be explored are free of obstructions. However, the
use of MAPF to achieve their goals often faces static barriers,
and even other agents can also be considered dynamic
barriers. Because it requires some constraints in the program,
such as agents cannot collide with each other. The use of
single-agent can find the shortest path through exploration.
Still, multi-agent cooperation should shorten the time to find
a target location, especially if there is more than one target.
This paper explains the Systematic Literature Review (SLR)
method to review research on various multi-agent
pathfinding. The contribution of this paper is the analysis of
multi-agent pathfinding and its potential application in
solving maze problems based on an SLR. |
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