DSSE: a drone swarm search environment
This provides a new benchmark for studying reinforcement learning algorithms that handle dynamic probabilities, but it is incremental as it builds on existing frameworks like PettingZoo.
The authors introduced DSSE, a drone swarm search environment based on PettingZoo, designed for multi-agent or single-agent reinforcement learning where drones must locate targets (e.g., shipwrecked people) using dynamic probability inputs without direct distance rewards.
The Drone Swarm Search project is an environment, based on 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 study of reinforcement learning algorithms that require dynamic probabilities as inputs.