Title
Cognitive Models Of Decision Making Processes For Human-Robot Interaction
Keywords
ACT-R; cognitive architectures; cognitive modeling; decision trees; Human-robot interaction; shared mental models
Abstract
A fundamental aspect of human-robot interaction is the ability to generate expectations for the decisions of one's teammate(s) in order to coordinate plans of actions. Cognitive models provide a promising approach by allowing both a robot to model a human teammate's decision process as well as by modeling the process through which a human develops expectations regarding its robot partner's actions. We describe a general cognitive model developed using the ACT-R cognitive architecture that can apply to any situation that could be formalized using decision trees expressed in the form of instructions for the model to execute. The model is composed of three general components: instructions on how to perform the task, situational knowledge, and past decision instances. The model is trained using decision instances from a human expert, and its performance is compared to that of the expert. © 2013 Springer-Verlag Berlin Heidelberg.
Publication Date
1-1-2013
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
8021 LNCS
Issue
PART 1
Number of Pages
285-294
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-642-39405-8_32
Copyright Status
Unknown
Socpus ID
84884852116 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84884852116
STARS Citation
Lebiere, Christian; Jentsch, Florian; and Ososky, Scott, "Cognitive Models Of Decision Making Processes For Human-Robot Interaction" (2013). Scopus Export 2010-2014. 7711.
https://stars.library.ucf.edu/scopus2010/7711