arXiv:2307.06240v2 Announce Type: replace Abstract: The Drone Swarm Search project is an environment, based on \textsc{PettingZoo}, that is to be used in conjunction with multi-agent (or single-agent) reinforcement learning algorithms. It is an environment in which the agents (drones), have to find the targets (shipwrecked people). The agents do not know the position of the target and do not receive rewards related to their own distance to the target(s). However, the agents receive the probabilities of the target(s) being in a certain cell of the map. The aim of this project is to aid in the s
The proliferation of drone technology and advancements in multi-agent reinforcement learning are converging to enable sophisticated swarm intelligence applications.
This development can significantly enhance search and rescue operations, enabling faster and more efficient detection of targets in complex environments, with implications for military and civil applications.
The ability to deploy autonomous, coordinated drone swarms for reconnaissance and search missions is becoming more practical and accessible through open-source environments like DSSE.
- · Search and rescue organizations
- · Defence sectors
- · AI/ML developers
- · Drone manufacturers
- · Traditional manual search operations
Increased efficiency and reduced risk in search and rescue missions due to autonomous drone swarm deployment.
Accelerated development and adoption of AI-driven multi-agent systems in various real-world scenarios beyond search operations.
Ethical and regulatory discussions intensify regarding autonomous swarms, particularly in defence and surveillance contexts, due to their increasing capabilities.
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