The CxBR Diffusion Engine -- A Tool for Modeling Human Behavior on the Battle Field

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Fernlund:2004:SAWMAS,

• author = "Hans Fernlund and Sven Eklund and Avelino J. Gonzalez",
• title = "The {CxBR} Diffusion Engine -- A Tool for Modeling Human Behavior on the Battle Field",
• booktitle = "The Second Swedish-American Workshop on Modeling and Simulation, SAWMAS-2004",
• year = "2004",
• editor = "Avelino J. Gonzalez and Johan Jenvald and Soren Palmgren",
• address = "Holiday Inn, Cocoa Beach, Florida",
• month = feb # " 2-3",
• keywords = "genetic algorithms, genetic programming",
• annote = "The Pennsylvania State University CiteSeerX Archives",
• bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
• language = "en",
• oai = "oai:CiteSeerX.psu:10.1.1.454.2112",
• 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",
• URL = "http://www.mind.foi.se/SAWMAS/SAWMAS-2004/Papers/P10-SAWMAS-2004-H-Fernlund.pdf",
• 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.",
• notes = "http://www.mind.foi.se/SAWMAS/SAWMAS-2004/index.html",

}

Genetic Programming entries for Hans Fernlund Sven E Eklund Avelino J Gonzalez

Citations