Repository logo
 

Reducing goal state divergence with environment design

dc.contributor.authorSikes, Kelsey, author
dc.contributor.authorSreedharan, Sarath, advisor
dc.contributor.authorBlanchard, Nathaniel, committee member
dc.contributor.authorChong, Edwin K.P., committee member
dc.date.accessioned2025-09-01T10:42:02Z
dc.date.available2025-09-01T10:42:02Z
dc.date.issued2025
dc.description.abstractAt the core of most successful human-robot collaborations is alignment between a robot's behavior and a human's expectations. Achieving this alignment is often difficult, however, because without careful specification, a robot may misinterpret a human's goals, causing it to perform actions with unexpected, if not dangerous side effects. To avoid this, I propose a new metric called Goal State Divergence (GSD), which represents the difference between the final goal state achieved by a robot and the one a human user expected. In cases where GSD cannot be directly calculated, I show how it can be approximated using maximal and minimal bounds. I then leverage GSD in my novel human-robot goal alignment design (HRGAD) problem, which identifies a minimal set of environment modifications that can reduce such mismatches. To illustrate the effectiveness of my method for reducing goal state divergence, I then empirically evaluate it on several standard planning benchmarks.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierSikes_colostate_0053N_19072.pdf
dc.identifier.urihttps://hdl.handle.net/10217/241759
dc.identifier.urihttps://doi.org/10.25675/3.02079
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectclassical planning
dc.subjectgoal recognition
dc.subjectplanning and scheduling
dc.subjectenvironment design
dc.subjectautomated planning
dc.subjecthuman-robot interaction
dc.titleReducing goal state divergence with environment design
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineComputer Science
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Sikes_colostate_0053N_19072.pdf
Size:
2.37 MB
Format:
Adobe Portable Document Format