TY - JOUR
T1 - Prognostic normative reasoning
AU - Oh, Jean
AU - Meneguzzi, Felipe
AU - Sycara, Katia
AU - Norman, Timothy J.
N1 - Funding Information:
Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053 . The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.
PY - 2013/2
Y1 - 2013/2
N2 - Human users planning for multiple objectives in complex environments are subjected to high levels of cognitive workload, which can severely impair the quality of the plans created. This paper describes a software agent that can proactively assist cognitively overloaded users by providing normative reasoning about prohibitions and obligations so that the user can focus on her primary objectives. In order to provide proactive assistance, we develop the notion of prognostic normative reasoning (PNR) that consists of the following steps: (1) recognizing the user's planned activities, (2) reasoning about norms to evaluate those predicted activities, and (3) providing necessary assistance so that the user's activities are consistent with norms. The idea of PNR integrates various AI techniques, namely, user intention recognition, normative reasoning over a user's intention, and planning, execution and replanning for assistive actions. In this paper, we describe an agent architecture for PNR and discuss practical applications.
AB - Human users planning for multiple objectives in complex environments are subjected to high levels of cognitive workload, which can severely impair the quality of the plans created. This paper describes a software agent that can proactively assist cognitively overloaded users by providing normative reasoning about prohibitions and obligations so that the user can focus on her primary objectives. In order to provide proactive assistance, we develop the notion of prognostic normative reasoning (PNR) that consists of the following steps: (1) recognizing the user's planned activities, (2) reasoning about norms to evaluate those predicted activities, and (3) providing necessary assistance so that the user's activities are consistent with norms. The idea of PNR integrates various AI techniques, namely, user intention recognition, normative reasoning over a user's intention, and planning, execution and replanning for assistive actions. In this paper, we describe an agent architecture for PNR and discuss practical applications.
KW - Agent architecture
KW - Normative reasoning
KW - Proactive agents
UR - http://www.scopus.com/inward/record.url?scp=84872681489&partnerID=8YFLogxK
U2 - 10.1016/j.engappai.2012.12.006
DO - 10.1016/j.engappai.2012.12.006
M3 - Article
AN - SCOPUS:84872681489
VL - 26
SP - 863
EP - 872
JO - Engineering Applications of Artificial Intelligence
JF - Engineering Applications of Artificial Intelligence
SN - 0952-1976
IS - 2
ER -