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

Sycara, Katia and Lebiere, Christian and Pei, Yulong and Morrison, Donald and Lewis, Michael (2015) Abstraction of analytical models from cognitive models of human control of robotic swarms. In: International Conference on Cognitive Modeling.

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Abstract

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 overfitting and lack of generalization. We introduce a methodology for deriving formal models of human control of cyber-physical 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 (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Sycara, Katia
Lebiere, Christian
Pei, Yulong
Morrison, Donald
Lewis, Michael
Date: 2015
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: International Conference on Cognitive Modeling
Event Title: International Conference on Cognitive Modeling
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Official URL: http://www.iccm2015.org/proceedings/papers/0003/pa...
Date Deposited: 08 Jun 2015 17:58
Last Modified: 01 Nov 2017 12:55
URI: http://d-scholarship.pitt.edu/id/eprint/25320

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