165 research outputs found
Emergence of Leadership in Communication
We study a neuro-inspired model that mimics a discussion (or information
dissemination) process in a network of agents. During their interaction, agents
redistribute activity and network weights, resulting in emergence of leader(s).
The model is able to reproduce the basic scenarios of leadership known in
nature and society: laissez-faire (irregular activity, weak leadership, sizable
inter-follower interaction, autonomous sub-leaders); participative or
democratic (strong leadership, but with feedback from followers); and
autocratic (no feedback, one-way influence). Several pertinent aspects of these
scenarios are found as well---e.g., hidden leadership (a hidden clique of
agents driving the official autocratic leader), and successive leadership (two
leaders influence followers by turns). We study how these scenarios emerge from
inter-agent dynamics and how they depend on behavior rules of agents---in
particular, on their inertia against state changes.Comment: 17 pages, 11 figure
Modeling and Mathematical Analysis of Swarms of Microscopic Robots
The biologically-inspired swarm paradigm is being used to design
self-organizing systems of locally interacting artificial agents. A major
difficulty in designing swarms with desired characteristics is understanding
the causal relation between individual agent and collective behaviors.
Mathematical analysis of swarm dynamics can address this difficulty to gain
insight into system design. This paper proposes a framework for mathematical
modeling of swarms of microscopic robots that may one day be useful in medical
applications. While such devices do not yet exist, the modeling approach can be
helpful in identifying various design trade-offs for the robots and be a useful
guide for their eventual fabrication. Specifically, we examine microscopic
robots that reside in a fluid, for example, a bloodstream, and are able to
detect and respond to different chemicals. We present the general mathematical
model of a scenario in which robots locate a chemical source. We solve the
scenario in one-dimension and show how results can be used to evaluate certain
design decisions.Comment: 2005 IEEE Swarm Intelligence Symposium, Pasadena, CA June 200
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