A Decision-Theoretic Approach to Cooperative Control and Adjustable Autonomy

被引：4

作者：

Mouaddib, Abdel-Illah ^{[1
]}

Zilberstein, Shlomo ^{[1
]}

Beynier, Aurelie ^{[1
]}

Jeanpierre, Laurent ^{[1
]}

机构：

[1] Univ Caen Basse Normandie, GREYC, Caen, France

来源：

ECAI 2010 - 19TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2010年 / 215卷

关键词：

D O I：

10.3233/978-1-60750-606-5-971

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Cooperative control can help overcome the limitations of autonomous systems (AS) by introducing a supervision unit (SU) (human or another system) into the control loop and creating adjustable autonomy. We present a decision-theoretic approach to accomplish this using Mixed Markov Decision Processes (MI-MDPs). The solution is an optimal plan that tells the AS what actions to perform as well as when to request SU attention or transfer control to the SU. This provides a varying degree of autonomy, particularly suitable for robots exploring a domain with regions that are too complex or risky for autonomous operation, or intelligent vehicles operating in heavy traffic.

引用

页码：971 / +

页数：2