Validation of cognitive models for collaborative hybrid systems with discrete human input

Vinod, AP and Tang, Y and Oishi, MMK and Sycara, K and Lebiere, C and Lewis, M (2016) Validation of cognitive models for collaborative hybrid systems with discrete human input. In: UNSPECIFIED.

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Abstract

We present a method to validate a cognitive model, based on the cognitive architecture ACT-R, in dynamic humanautomation systems with discrete human input. We are inspired by the general problem of K-choice games as a proxy for many decision making applications in dynamical systems. We model the human as a Markovian controller based on gathered experimental data, that is, a non-deterministic control input with known likelihoods of control actions associated with certain configurations of the state-space. We use reachability analysis to predict the outcome of the resulting discrete-time stochastic hybrid system, in which the outcome is defined as a function of the system trajectory. We suggest that the resulting expected outcomes can be used to validate the cognitive model against actual human subject data. We apply our method to a twochoice game in which the human is tasked with maximizing net coverage of a robotic swarm that can operate under rendezvous or deployment dynamics. We validate the corresponding ACTR cognitive model generated with the data from eight human subjects. The novelty of this work is 1) a method to compute expected outcome in a hybrid dynamical system with a Markov chain model of the human's discrete choice, and 2) application of this method to validation of cognitive models with a database of actual human subject data.

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Details

Item Type:	Conference or Workshop Item (UNSPECIFIED)
Status:	Published
Creators/Authors:	Creators Email Pitt Username ORCID Vinod, AP Tang, Y Oishi, MMK Sycara, K Lebiere, C Lewis, M
Date:	28 November 2016
Date Type:	Publication
Journal or Publication Title:	IEEE International Conference on Intelligent Robots and Systems
Volume:	2016-N
Page Range:	3339 - 3346
Event Type:	Conference
DOI or Unique Handle:	10.1109/iros.2016.7759514
Schools and Programs:	School of Information Sciences > Information Science
Refereed:	Yes
ISBN:	9781509037629
ISSN:	2153-0858
Date Deposited:	30 Jun 2017 15:10
Last Modified:	05 Sep 2023 11:57
URI:	http://d-scholarship.pitt.edu/id/eprint/31544

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