DSSE: a drone swarm search environment

TL;DR

The paper introduces DSSE, a drone swarm search environment based on PettingZoo, designed to facilitate reinforcement learning research involving dynamic probabilistic inputs for multi-agent search tasks.

Contribution

It presents a new simulation environment tailored for reinforcement learning with dynamic probability inputs in multi-agent search scenarios.

Findings

Environment supports multi-agent drone search tasks

Designed for reinforcement learning with probabilistic inputs

Facilitates research on dynamic probability-based decision making

Abstract

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.