Paper Info
Title
Hierarchical Expertise-Level Modeling for User Specific Robot-Behavior Explanations.
Abstract
There is a growing interest within the AI research community to develop autonomous systems capable of explaining their behavior to users. One aspect of the explanation generation problem that has yet to receive much attention is the task of explaining plans to users whose level of expertise differ from that of the explainer. We propose an approach for addressing this problem by representing the useru0027s model as an abstraction of the domain model that the planner uses. We present algorithms for generating minimal explanations in cases where this abstract human model is not known. We reduce the problem of generating explanation to a search over the space of abstract models and investigate possible greedy approximations for minimal explanations. We also empirically show that our approach can efficiently compute explanations for a variety of problems.
Year
Venue
Field
2018
arXiv: Artificial Intelligence
Abstraction,Computer science,Planner,Autonomous system (Internet),Artificial intelligence,Behavior-based robotics,Domain model,Machine learning
DocType
Volume
Citations 
Journal
abs/1802.06895
2
PageRank 
References 
Authors
0.39
10
3
Name
Order
Citations
PageRank
Sarath Sreedharan1309.83
Siddharth Srivastava221025.98
Subbarao Kambhampati33453450.74