main research projects
My research focuses on analysis and modeling of collective behavior in complex biological systems and development of algorithms for multi agent systems. Physical and mathematical modeling and computer simulations are used to study the macroscopic behavior of groups in nature. The research aims at finding the underlying mechanisms of the behavior in order to be able to understand and even control such groups and to use similar mechanisms, adopted from natural collective behavior, for multi agent systems.
Complex Collective Navigation in Bacteria-Inspired Models
Modeling Bacteria Collective Motion Dynamics
We study movement dynamics, group pattern, and communication in bacteria colonies. A bacteria colony can consists of 109 single bacterium. These colonies display intricate dynamics and pattern under stress conditions and are able to efficiently solve difficult search tasks in noisy and uneven environments. We use physical modeling to study the behavior of a large number of agents inspired by the natural behavior of bacteria. One such model, currently under development, is designed to reproduce different types of dynamics seen in experiments of lubricating bacteria.
Many groups in nature, including bacteria, sense and respond to the environment in a decentralized manner, as distributed information processing systems. I studied the effect of adaptive interactions on the speed and quality of decision making in a group of moving agents. Results showed that adaptive groups form a coherent motion in the direction of the global gradient faster and more accurately than previous models (Shklarsh et al, PlosComputational Biology, 2011). Cargo transport, such as fungal spores, was investigated in such models (Shklarsh et al, Interface Focus, 2012). We are now going further, to understand navigation in terrains with obstacles, such as a maze.
Theoretical analysis of collective behavior.
We study the theoretical basis of self organization and emergent behavior in groups of moving elements. We describe, model, and analyze general phenomenon such as leadership, decision making, cooperation, and competition in swarms and its implications to evolution, game theory, and computer science.
Bacteria game theory
Bacteria have many cell fates. They can stay vegetative, a form which may lead to all other fates, become a spore, become cannibalistic by producing a toxin that harm bacteria around them, and more. We view this as game strategies in a group of agents in the context of game theory.