Towards the portability of knowledge in reinforcement learning-based systems for automatic drone navigation.

ABSTRACT: In the field of artificial intelligence (AI) one of the main challenges today is to make the knowledge acquired when performing a certain task in a given scenario applicable to similar yet different tasks to be performed with a certain degree of precision in other environments. This idea of knowledge portability is of great use in Cyber-Physical Systems (CPS) that face important challenges in terms of reliability and autonomy. This article presents a CPS where unmanned vehicles (drones) are equipped with a reinforcement learning system so they may automatically learn to perform various navigation tasks in environments with physical obstacles. The implemented system is capable of isolating the agents' knowledge and transferring it to other agents that do not have prior knowledge of their en

SUBMITTER: Barreiro JM 

PROVIDER: S-EPMC10280651 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature