Publications

Garcia, Rudy J.; Ma, Tian J.; Sandoval, Ness S.; Antognoli, Matthew; Rackley, Nathanael P.

Abstract not provided.

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.

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.

Cooper, Curtis S.; Hobbs, Jacob A.; Beyeler, Walter E.; Antognoli, Matthew

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.