Faculty Advisor or Committee Member

Charles Rich, Advisor

Faculty Advisor or Committee Member

Sonia Chernova, Advisor

Identifier

etd-091015-114432

Abstract

"This thesis presents learning and interaction algorithms to support a human teaching hierarchical task models to a robot using a single or multiple examples in the context of a mixed-initiative interaction with bi-directional communication. Our first contribution is an approach for learning a high level task from a single example using the bottom-up style. In particular, we have identified and implemented two important heuristics for suggesting task groupings and repetitions based on the data flow between tasks and on the physical structure of the manipulated artifact. We have evaluated our heuristics with users in a simulated environment and shown that the suggestions significantly improve the learning and interaction. For our second contribution, we extended this interaction by enabling users to teaching tasks using the top-down teaching style in addition to the bottom-up teaching style. Results obtained in a pilot study show that users utilize both the bottom-up and the top-down teaching styles to teach tasks. Our third contribution is an algorithm that merges multiple examples when there are alternative ways of doing a task. The merging algorithm is still under evaluation. "

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Computer Science

Project Type

Thesis

Date Accepted

2015-09-10

Accessibility

Unrestricted

Subjects

mixed-initiative interaction, Learning from Demonstration, Learning from Instructions, Hierarchical Task Networks, collaborative discourse theory

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