Title
A developmentally inspired transfer learning approach for predicting skill durations
Abstract
As robots are increasingly integrated into daily life, one of the most important roles they will assume is that of collaboratively helping us perform physical tasks. Be it helping us put together furniture, transporting materials, or assisting with food preparation, a system's ability to assess its (and others') skill level regarding the performance of different tasks is essential to achieving efficient scheduling and collaboration. In this paper, we present preliminary work towards an observation-driven modeling approach allowing an agent to autonomously predict the amount of time required for different agents to complete actions. This approach utilizes insights and observations from the developmental psychology and operations research communities to accurately develop agent-personalized skill proficiency models. We demonstrate our model by evaluating its performance at estimating agent performance in a set of common assembly tasks. Our evaluation measures knowledge-transfer via novel task introduction, as well as extrapolation by predicting future performance given previous experience.
Year
DOI
Venue
2014
10.1109/DEVLRN.2014.6982979
ICDL-EPIROB
Keywords
Field
DocType
extrapolation,intelligent robots,learning systems,service robots,agent performance estimation,agent-personalized skill proficiency models,assembly tasks,developmental psychology,future performance prediction,knowledge-transfer,observation-driven modeling approach,operations research communities,performance evaluation,physical tasks,robots,skill duration prediction,transfer learning approach,predictive models,estimation,computational modeling,psychology,assembly
Computer science,Scheduling (computing),Transfer of learning,Knowledge transfer,Artificial intelligence,Robot,Machine learning
Conference
Citations 
PageRank 
References 
1
0.38
4
Authors
5
Name
Order
Citations
PageRank
Bradley Hayes1659.58
Elena Corina Grigore2164.50
alexandru litoiu310.38
Aditi Ramachandran4213.80
B. Scassellati51735241.11