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H. Van Dyke Parunak
AxonAI, Inc.
Harrisonburg, Virginia
 

H. Van Dyke Parunak is Vice President for Technology Innovation at AxonAI, Inc. He has extensive experience in both academic and industrial environments with chaos and complex systems, artificial intelligence, distributed computing, and human interfaces. Since 1984, he led the Agent-based and Complex Systems Research group, housed since 1984 in a variety of companies, studying swarm intelligence, emergent behavior, and nonlinear dynamics. In 2013, AxonAI was formed to commercialize these results.

His major research accomplishments include fine-grained agent architectures for a variety of manufacturing and defense functions, emphasizing applications of nonlinear dynamics and chaos theory to analyzing and controlling agent communities. He and his colleagues develop applications that take advantage of the self-organizing potential of very simple agents when they interact through a shared environment, inspired by examples in biological and ecological systems. He is the author or co-author of more than 200 technical articles and reports, and the coinventor on 13 patents in the area of agent technology.

Parunak has worked as a project designer and associate investigator at Harvard University, as an Assistant Professor and Postdoctoral Scholar at the University of Michigan, and as a computer scientist with Comshare, Inc. His research was done at the Industrial Technology Institute, ERIM, Altarum, NewVectors, TechTeam Government Solutions, Jacobs Technology Group, and Soar Technology. He received an AB in Physics from Princeton University (1969), an MS in Computer and Communication Sciences from the University of Michigan (1982), and a PhD in Near Eastern Languages and Civilizations from Harvard University (1978). He is a member of the American Association for Artificial Intelligence and the Association for Computing Machinery.

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Updated March 1, 2016


     

Modeling and simulation with Compose and Activate
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This volume offers a detailed look at a new environment for systems modeling based on the open matrix language (OML), a relatively new language for numerical computation in the tradition of MATLAB, Octave, Scilab, and Julia. The environment includ...

 

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Stochastic computing is an approach to numerical computing that dates back to von Neumann’s work on probabilistic logics in 1952, and that requires far fewer transistors than conventional numerical processing. This economy led to extensive r...

 

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Humans are not the rational optimizers posited by classical economics or the axiomatic game theory of von Neumann and Morgenstern. Since 2012, the Center for Adaptive Rationality at the Max Planck Institute for Human Development in Berlin has been...

 

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Evertsz R., Thangarajah J., Ly T.,  Springer International Publishing, New York, NY, 2019. 116 pp. Type: Book (978-3-319951-94-2)

Computational models hold considerable promise for planning and prediction in applied domains such as military operations. But such models face a knowledge acquisition bottleneck when applying them to complex real-world problems. For example, agen...

 
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