Publications

Kuypers, Marshall A.; Beyeler, Walter E.; Antognoli, Matthew; Glass, Robert J.

Abstract not provided.

Beyeler, Walter E.; Antognoli, Matthew; Glass, Robert J.

Abstract not provided.

Finley, Patrick D.; Glass, Robert J.; Hammer, Ryan H.

Abstract not provided.

Finley, Patrick D.; Lambert, Gregory J.; Glass, Robert J.

Abstract not provided.

Antognoli, Matthew; Kuypers, Marshall A.; Beyeler, Walter E.; Glass, Robert J.

Abstract not provided.

Beyeler, Walter E.; Antognoli, Matthew; Kuypers, Marshall A.; Glass, Robert J.

Abstract not provided.

Antognoli, Matthew; Kuypers, Marshall A.; Beyeler, Walter E.; Glass, Robert J.

Abstract not provided.

Beyeler, Walter E.; Antognoli, Matthew; Glass, Robert J.

Abstract not provided.

Beyeler, Walter E.; Antognoli, Matthew; Glass, Robert J.

Abstract not provided.

Beyeler, Walter E.; Kuypers, Marshall A.; Antognoli, Matthew; Glass, Robert J.

Abstract not provided.

Beyeler, Walter E.; Glass, Robert J.; Antognoli, Matthew

Abstract not provided.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Mitchell, Michael D.; Beyeler, Walter E.; Glass, Robert J.; Antognoli, Matthew; Moore, Thomas W.

Competition is fierce and often the first to act has an advantage, especially in environments where there are excess resources. However, expanding quickly to absorb excess resources creates requirements that might be unmet in future conditions of scarcity. Different patterns of scarcity call for different strategies. We define a model of interacting specialists (entities) to analyze which sizing strategies are most successful in environments subjected to frequent periods of scarcity. We require entities to compete for a common resource whose scarcity changes periodically, then study the viability of entities following three different strategies through scarcity episodes of varying duration and intensity. The three sizing strategies are: aggressive, moderate, and conservative. Aggressive strategies are most effective when the episodes of scarcity are shorter and moderate; conversely, conservative strategies are most effective in cases of longer or more severe scarcity. © 2012 Springer-Verlag.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Kuypers, Marshall A.; Beyeler, Walter E.; Glass, Robert J.; Antognoli, Matthew; Mitchell, Michael D.

Complex adaptive systems (CAS) modeling has become a common tool to study the behavioral dynamics of agents in a broad range of disciplines from ecology to economics. Many modelers have studied structure's importance for a system in equilibrium, while others study the effects of perturbations on system dynamics. There is a notable absence of work on the effects of agent interaction pathways on perturbation dynamics. We present an agent-based CAS model of a competitive economic environment. We use this model to study the perturbation dynamics of simple structures by introducing a series of disruptive events and observing key system metrics. Then, we generate more complex networks by combining the simple component structures and analyze the resulting dynamics. We find the local network structure of a perturbed node to be a valuable indicator of the system response. © 2012 Springer-Verlag.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Moore, Thomas W.; Finley, Patrick D.; Hammer, Ryan H.; Glass, Robert J.

International forces in Afghanistan have experienced difficulties in developing constructive engagements with the Afghan population, an experience familiar to a wide range of international agencies working in underdeveloped and developing nations around the world. Recently, forces have begun deploying Female Engagement Teams, female military units who engage directly with women in occupied communities, resulting inmore positive relationships with those communities as a whole. In this paper, we explore the hypothesis that the structure of community-based social networks strongly contributes to the effectiveness of the Female Engagement Team strategy, specifically considering gender-based differences in network community structure. We find that the ability to address both female and male network components provides a superior ability to affect opinions in the network, and can provide an effective means of counteracting influences from opposition forces. © 2012 Springer-Verlag.

Finley, Patrick D.; Hammer, Ryan H.; Glass, Robert J.

Abstract not provided.

Linebarger, John M.; Detry, Richard J.; Glass, Robert J.; Beyeler, Walter E.; Ames, Arlo L.; Finley, Patrick D.

Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

Proposed for publication in Journal of Intelligence Community Research and Development.

Schubert, Janis S.; Finley, Patrick D.; Hammer, Ryan H.; Glass, Robert J.

Abstract not provided.

Watson Ross, Chrys M.; Glass, Robert J.; Harger, John R.; Conrad, Stephen H.; Zagonel, Aldo A.; Beyeler, Walter E.; Finley, Melissa F.

Abstract not provided.

Beyeler, Walter E.; Glass, Robert J.; Finley, Patrick D.; Quach, Tu-Thach Q.

Infrastructures are networks of dynamically interacting systems designed for the flow of information, energy, and materials. Under certain circumstances, disturbances from a targeted attack or natural disasters can cause cascading failures within and between infrastructures that result in significant service losses and long recovery times. Reliable interdependency models that can capture such multi-network cascading do not exist. The research reported here has extended Sandia's infrastructure modeling capabilities by: (1) addressing interdependencies among networks, (2) incorporating adaptive behavioral models into the network models, and (3) providing mechanisms for evaluating vulnerability to targeted attack and unforeseen disruptions. We have applied these capabilities to evaluate the robustness of various systems, and to identify factors that control the scale and duration of disruption. This capability lays the foundation for developing advanced system security solutions that encompass both external shocks and internal dynamics.

Brown, Theresa J.; Glass, Robert J.; Beyeler, Walter E.; Ames, Arlo L.; Linebarger, John M.

Complex Adaptive Systems of Systems, or CASoS, are vastly complex eco-socio-economic-technical systems which we must understand to design a secure future for the nation and the world. Perturbations/disruptions in CASoS have the potential for far-reaching effects due to highly-saturated interdependencies and allied vulnerabilities to cascades in associated systems. The Phoenix initiative approaches this high-impact problem space as engineers, devising interventions (problem solutions) that influence CASoS to achieve specific aspirations. CASoS embody the world's biggest problems and greatest opportunities: applications to real world problems are the driving force of our effort. We are developing engineering theory and practice together to create a discipline that is grounded in reality, extends our understanding of how CASoS behave, and allows us to better control those behaviors. Through application to real-world problems, Phoenix is evolving CASoS Engineering principles while growing a community of practice and the CASoS engineers to populate it.

Glass, Robert J.; Ames, Arlo L.; Brown, Theresa J.; Linebarger, John M.; Beyeler, Walter E.

Complex Adaptive Systems of Systems, or CASoS, are vastly complex ecological, sociological, economic and/or technical systems which we must understand to design a secure future for the nation and the world. Perturbations/disruptions in CASoS have the potential for far-reaching effects due to pervasive interdependencies and attendant vulnerabilities to cascades in associated systems. Phoenix was initiated to address this high-impact problem space as engineers. Our overarching goals are maximizing security, maximizing health, and minimizing risk. We design interventions, or problem solutions, that influence CASoS to achieve specific aspirations. Through application to real-world problems, Phoenix is evolving the principles and discipline of CASoS Engineering while growing a community of practice and the CASoS engineers to populate it. Both grounded in reality and working to extend our understanding and control of that reality, Phoenix is at the same time a solution within a CASoS and a CASoS itself.

Finley, Patrick D.; Brown, Theresa J.; Zagonel, Aldo A.; Glass, Robert J.

Abstract not provided.

Glass, Robert J.; Harger, John R.; Conrad, Stephen H.; Zagonel, Aldo A.; Beyeler, Walter E.; Finley, Melissa F.

Abstract not provided.

Outkin, Alexander V.; Glass, Robert J.

Abstract not provided.

Schubert, Janis S.; Finley, Patrick D.; Hammer, Ryan H.; Glass, Robert J.

Abstract not provided.