The CxBR Diffusion Engine -- A Tool for Modeling Human Behavior on the Battle Field
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Fernlund:2004:SAWMAS,
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author = "Hans Fernlund and Sven Eklund and
Avelino J. Gonzalez",
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title = "The {CxBR} Diffusion Engine -- A Tool for Modeling
Human Behavior on the Battle Field",
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booktitle = "The Second Swedish-American Workshop on Modeling and
Simulation, SAWMAS-2004",
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year = "2004",
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editor = "Avelino J. Gonzalez and Johan Jenvald and
Soren Palmgren",
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address = "Holiday Inn, Cocoa Beach, Florida",
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month = feb # " 2-3",
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keywords = "genetic algorithms, genetic programming",
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annote = "The Pennsylvania State University CiteSeerX Archives",
-
bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.454.2112",
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pages = "10",
-
rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
-
URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.454.2112",
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URL = "http://www.mind.foi.se/SAWMAS/SAWMAS-2004/Papers/P10-SAWMAS-2004-H-Fernlund.pdf",
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abstract = "The option to automatically model the behaviour of
different actors during live exercise training would
increase the value of the after-action-review (AAR)
process. If a simulated model of the actors is
available right after the live exercise training, the
evaluation of their behaviour would be more timely and
alternative actions could also be evaluated at the same
time. The CxBR Diffusion Engine merges technologies to
establish a tool for automatic, on-line behaviour
modelling. Context Based Reasoning (CxBR) is a proven
methodology to build simulated agents with human
behaviour. Genetic Programming (GP) provides the CxBR
framework with learning capabilities to automatically
create simulated agents with human behaviour. The final
piece in the CxBR Diffusion Engine is to provide an
efficient, flexible, scaleable and mobile platform to
evolve the agents behaviour. This platform is the newly
developed massively parallel architecture for
distributed GP. The massively parallel architecture has
the potential to execute the GP linear machine code
representation at a rate of up to 50,000 generations
per second. Implemented in an FPGA, this architecture
is highly portable and applicable to mobile, on-line
applications. This paper will present a theory on how
the CxBR + GP can evolve simulated agents with human
behaviour by observation in a massively parallel
architecture. These pieces will introduce all the
necessary elements to build the CxBR Diffusion Engine
that could model human behaviour to enable individual
AAR of trainees in the training field.",
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notes = "http://www.mind.foi.se/SAWMAS/SAWMAS-2004/index.html",
- }
Genetic Programming entries for
Hans Fernlund
Sven E Eklund
Avelino J Gonzalez
Citations