|
Abstract:
This paper describes a research plan that will examine the linkage between the physical and human (cognitive and social) domains of a network as they relate to human decision-making. This strategy has three components: theory, computation/simulation and experiment/observation. We will extend the most recent methods of statistical physics to non-stationary, renewal stochastic processes that appear to be characteristic of the interactions among nodes in complex networks and we will pursue the phenomenon of synchronization, whose mathematical formulation has recently provided insight into how complex networks reach accommodation and cooperation. The theoretical analyses of complex networks often elude analytic solutions and require large-scale simulation and computation to analyze the underlying dynamic process. We will use agent-based modeling to simulate the dynamics of such complex networks, particularly models of dynamic decision-making under conflicting constraints and with incomplete information. We will develop decision-making scenarios from which to extract large amounts of data for analysis, for the development of theoretical models and the construction of large-scale computer simulations, as well as, optimal data processing techniques to guide the theoretical analysis. We expect that the theory, computation/simulation and experiment/observation components will inform and refine one another in an iterative way through intense collaboration.
| Limitations: |
 APPROVED FOR PUBLIC RELEASE |
| Description: |
Conference paper with briefing charts |
| Pages: |
33 |
| Report Date: |
01-Jun-2008 |
| Report Number: |
A257684 |
|
|
|
|
|
Keywords relating to this report:
Email This Abstract
