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Uncertainty-Aware and Temporally Regulated Expert Advice in Reinforcement Learning for Autonomous Driving

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arXiv:2605. 30576v1 Announce Type: new Abstract: Exploration in reinforcement learning for autonomous driving is inherently unsafe: agents must experience novel behaviors to learn, yet exploration can lead to collisions or off-road driving.

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Authors: Ahmed Abouelazm, Felix Klingebiel, Philip Sch\"orner, J. Marius Z\"ollner
Released: 2026-06-01 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Uncertainty-Aware and Temporally Regulated Expert Advice in Reinforcement Learning for Autonomous Driving overlaps with clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "Add C2 control arm (donor sees marker_B without marker_A) to disambiguate paired-marker binding from marker_B leaking alone", experiment "#351 follow-up: broader-vocab position-0 sweep at T=1.0 + position-1 suffix isolation". Matching terms: line, rate, without, lora. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2605.30576

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