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Abstraction of analytical models from cognitive models of human control of robotic swarms

Sycara, K and Lebiere, C and Pei, Y and Morrison, D and Tang, Y and Lewis, M (2015) Abstraction of analytical models from cognitive models of human control of robotic swarms. In: UNSPECIFIED.

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Abstract

© Proceedings of ICCM 2015 - 13th International Conference on Cognitive Modeling. In order to formally validate cyber-physical systems, analytically tractable models of human control are desirable. While those models can be abstracted directly from human data, limitations on the amount and reliability of data can lead to over-fitting and lack of generalization. We introduce a methodology for deriving formal models of human control of cyberphysical systems based on the use of cognitive models. Analytical models such as Markov models can be derived from an instance-based learning model of the task built using the ACT-R cognitive architecture. The approach is illustrated in the context of a robotic control task involving the choice of two options to control a robotic swarm. The cognitive model and various forms of the analytical model are validated against each other and against human performance data. The current limitations of the approach are discussed as well as its implications for the automated validation of cyber-physical systems.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Sycara, K
Lebiere, C
Pei, Y
Morrison, D
Tang, Y
Lewis, M
Date: 1 January 2015
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Proceedings of ICCM 2015 - 13th International Conference on Cognitive Modeling
Page Range: 13 - 18
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9789036777636
Date Deposited: 08 Jun 2015 17:58
Last Modified: 09 Jun 2020 12:55
URI: http://d-scholarship.pitt.edu/id/eprint/25320

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