A Review of Reward Functions for Reinforcement Learning in the context of Autonomous Driving

arXiv:2405.01440v1 Announce Type: cross
Abstract: Reinforcement learning has emerged as an important approach for autonomous driving. A reward function is used in reinforcement learning to establish the learned skill objectives and guide the agent toward the optimal policy. Since autonomous driving is a complex domain with partly conflicting objectives with varying degrees of priority, developing a suitable reward function represents a fundamental challenge. This paper aims to highlight the gap in such function design by assessing different proposed formulations in …

abstract agent arxiv autonomous autonomous driving context cs.ai cs.lg cs.ro domain driving function functions guide policy reinforcement reinforcement learning review skill type