Accession Number : ADA591084


Title :   Modeling Synergies in Large Human-Machine Networked Systems


Descriptive Note : Final rept. 1 Jul 2008-30 Jun 2013


Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA


Personal Author(s) : Sycara, Katia ; Lebiere, Christian ; Lewis, Michael ; Cummings, Mary ; How, Jonathan ; Campbell, Mark ; Scerri, Paul ; Parasuraman, Raja


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a591084.pdf


Report Date : 25 Sep 2013


Pagination or Media Count : 94


Abstract : Network centric military systems (NCW) involve hundreds to thousands of manned and autonomous entities cooperating to achieve complex joint objectives in incomplete information environments. The overall goal of this multidisciplinary research is to provide validated theories and models, grounded in experiments with human operators that allow descriptive and predictive characterization of important properties and performance of complex and large-scale human-machine networked systems. The most significant results of the research were: (a) a scalable cognitive model framework that provides scalability while maintaining targeted cognitive fidelity (b) algorithms for automated large scale path planning robot systems, (c) predicting behavior, including vulnerabilities, of large scale heterogeneous complex networks, (d) algorithms for constrained multi-robot task assignment (e) scalable models of human robot control for independently operating robots, (f) robot self-reflection and queuing algorithms to schedule operator attention, (g) scalable displays, (h) models of human-robot decision making,, (j) models for planning and resource allocation in multi-robot teams with formal performance guarantees, and (k) human-automation collaborative scheduling.


Descriptors :   *MAN MACHINE SYSTEMS , *NETWORKS , *SYNERGISM , ALGORITHMS , ALLOCATIONS , COGNITION , DECISION MAKING , MANNED , SCALING FACTOR


Subject Categories : Electrical and Electronic Equipment
      Operations Research
      Human Factors Engineering & Man Machine System


Distribution Statement : APPROVED FOR PUBLIC RELEASE