Human-in-the-Loop Reinforcement Learning: A Survey and Position on Requirements, Challenges, and Opportunities

Artificial intelligence (AI) and especially reinforcement learning (RL) have the potential to enable agents to learn and perform tasks autonomously with superhuman performance. However, we consider RL as fundamentally a Human-in-the-Loop (HITL) paradigm, even when an agent eventually performs its ta...

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Vydané v:	The Journal of artificial intelligence research Ročník 79; s. 359 - 415
Hlavní autori:	Retzlaff, Carl Orge, Das, Srijita, Wayllace, Christabel, Mousavi, Payam, Afshari, Mohammad, Yang, Tianpei, Saranti, Anna, Angerschmid, Alessa, Taylor, Matthew E., Holzinger, Andreas
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	San Francisco AI Access Foundation 01.01.2024
Predmet:	Agents (artificial intelligence) Artificial intelligence Explainable artificial intelligence Feedback Machine learning User experience Workflow
ISSN:	1076-9757, 1076-9757, 1943-5037
On-line prístup:	Získať plný text
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